language:

Find link is a tool written by Edward Betts.searching for Univariate (statistics) 262 found (266 total)

alternate case: univariate (statistics)

General linear model
(1,062 words)
[view diff]
no match in snippet
view article
find links to article

or as several independent univariate tests. In multivariate tests the columns of Y are tested together, whereas in univariate tests the columns of Y areUnivariate (281 words) [view diff] no match in snippet view article find links to article

fundamental properties of univariate polynomials that cannot be generalized to multivariate polynomials. The term is commonly used in statistics to distinguish aMultivariate statistics (1,242 words) [view diff] no match in snippet view article find links to article

practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order toTime series (4,165 words) [view diff] no match in snippet view article find links to article

time series analysis may also be divided into linear and non-linear, and univariate and multivariate. A time series is one type of panel data. Panel dataDescriptive statistics (863 words) [view diff] no match in snippet view article find links to article

investments in order to make better investing decisions in the future. Univariate analysis involves describing the distribution of a single variable, includingElliptical distribution (1,732 words) [view diff] no match in snippet view article find links to article

that have undefined mean, such as the Cauchy distribution (even in the univariate case). Because the variable x enters the density function quadraticallyUnivariate analysis (277 words) [view diff] no match in snippet view article find links to article

Univariate analysis is perhaps the simplest form of statistical analysis. Like other forms of statistics, it can be inferential or descriptive. The keyWilks's lambda distribution (635 words) [view diff] no match in snippet view article find links to article

In statistics, Wilks' lambda distribution (named for Samuel S. Wilks), is a probability distribution used in multivariate hypothesis testing, especiallyMultivariate analysis of variance (804 words) [view diff] no match in snippet view article find links to article

separately. MANOVA is a generalized form of univariate analysis of variance (ANOVA), although, unlike univariate ANOVA, it uses the covariance between outcomeUnivariate distribution (242 words) [view diff] no match in snippet view article find links to article

in statistics, a univariate distribution is a probability distribution of only one random variable. This is in contrast to a multivariate distributionGeneralized linear model (4,180 words) [view diff] no match in snippet view article find links to article

In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary linear regression that allows for response variables that haveMultivariate normal distribution (8,621 words) [view diff] no match in snippet view article find links to article

joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a randomProbability distribution (4,303 words) [view diff] no match in snippet view article find links to article

is called univariate, while a distribution whose sample space is a vector space of dimension 2 or more is called multivariate. A univariate distributionNormal distribution (20,050 words) [view diff] no match in snippet view article find links to article

probability theory, has been extended far beyond the standard framework of the univariate (that is one-dimensional) case (Case 1). All these extensions are alsoNatural exponential family (2,117 words) [view diff] no match in snippet view article find links to article

}}+\mathbf {t} )-A({\boldsymbol {\theta }})\,.} The five most important univariate cases are: normal distribution with known variance Poisson distributionHodges–Lehmann estimator (1,012 words) [view diff] no match in snippet view article find links to article

the populations. The Hodges–Lehmann univariate statistics have several generalizations in multivariate statistics: Multivariate ranks and signs SpatialExtreme value theory (2,424 words) [view diff] no match in snippet view article find links to article

that the limiting model is not as fully prescribed as in the univariate case. In the univariate case, the model (GEV distribution) contains three parametersCentral moment (1,280 words) [view diff] no match in snippet view article find links to article

also to its location. Sets of central moments can be defined for both univariate and multivariate distributions. The nth moment about the mean (or nthMultivariate t-distribution (1,174 words) [view diff] no match in snippet view article find links to article

of the Student's t-distribution, which is a distribution applicable to univariate random variables. While the case of a random matrix could be treated withinMedian absolute deviation (1,069 words) [view diff] no match in snippet view article find links to article

In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also referErrors and residuals (2,077 words) [view diff] no match in snippet view article find links to article

studentized residuals. Suppose there is a series of observations from a univariate distribution and we want to estimate the mean of that distribution (theDelta method (1,817 words) [view diff] no match in snippet view article find links to article

setting, careful motivation of the technique is more easily demonstrated in univariate terms. Roughly, if there is a sequence of random variables Xn satisfyingBivariate analysis (446 words) [view diff] no match in snippet view article find links to article

Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed. Like univariate analysis, bivariate analysis can be descriptiveNormal-inverse-gamma distribution (1,015 words) [view diff] no match in snippet view article find links to article

V − 1 {\displaystyle \sigma ^{2}\mathbf {V} ^{-1}} – while, as in the univariate case, σ 2 ∣ α , β ∼ Γ − 1 ( α , β ) {\displaystyle \sigma ^{2}\mid \alphaFive-number summary (735 words) [view diff] no match in snippet view article find links to article

data points are outliers. In order for these statistics to exist the observations must be from a univariate variable that can be measured on an ordinalBox–Jenkins method (1,530 words) [view diff] no match in snippet view article find links to article

whether the estimated model conforms to the specifications of a stationary univariate process. In particular, the residuals should be independent of each otherMathematical statistics (1,771 words) [view diff] no match in snippet view article find links to article

probability measures. A probability distribution can either be univariate or multivariate. A univariate distribution gives the probabilities of a single randomRepeated measures design (2,245 words) [view diff] no match in snippet view article find links to article

(Chapter 7)". Univariate and multivariate general linear models: Theory and applications with SAS (with 1 CD-ROM for Windows and UNIX). Statistics: TextbooksOrdinal data (2,521 words) [view diff] no match in snippet view article find links to article

statistical procedures. In place of means and standard deviations, univariate statistics appropriate for ordinal data include the median, other percentilesJMulTi (87 words) [view diff] no match in snippet view article find links to article

open-source interactive software for econometric analysis, specialised in univariate and multivariate time series analysis. It has a Java graphical user interfaceProbability density function (5,038 words) [view diff] no match in snippet view article find links to article

density function is most commonly associated with absolutely continuous univariate distributions. A random variable X {\displaystyle X} has density f X {\displaystyleTruncated normal distribution (1,874 words) [view diff] no match in snippet view article find links to article

Continuous univariate distributions-1, chapter 13. John Wiley & Sons. Lynch, Scott (2007). Introduction to Applied Bayesian Statistics and EstimationHotelling's T-squared distribution (2,203 words) [view diff] no match in snippet view article find links to article

multivariate statistics in undertaking tests of the differences between the (multivariate) means of different populations, where tests for univariate problemsGrubbs's test for outliers (578 words) [view diff] no match in snippet view article find links to article

extreme studentized deviate test, is a test used to detect outliers in a univariate data set assumed to come from a normally distributed population. Grubbs'sExponential dispersion model (864 words) [view diff] no match in snippet view article find links to article

are two versions to formulate an exponential disperson model. In the univariate case, a real-valued random variable X {\displaystyle X} belongs to theMedian (7,119 words) [view diff] no match in snippet view article find links to article

concepts that extend the definition of the univariate median; each such multivariate median agrees with the univariate median when the dimension is exactlyMultivariate kernel density estimation (4,207 words) [view diff] no match in snippet view article find links to article

density estimators were first introduced in the scientific literature for univariate data in the 1950s and 1960s and subsequently have been widely adoptedHigher-order statistics (265 words) [view diff] no match in snippet view article find links to article

robust than lower-order statistics. In statistical theory, one long-established approach to higher-order statistics, for univariate and multivariate distributionsRun chart (363 words) [view diff] no match in snippet view article find links to article

plots are an easy way to graphically summarize a univariate data set. A common assumption of univariate data sets is that they behave like: random drawings;Restricted maximum likelihood (427 words) [view diff] no match in snippet view article find links to article

implemented in Surfstat a Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric neuroimaging data using linearVine copula (2,769 words) [view diff] no match in snippet view article find links to article

multivariate distributions with uniform univariate margins. Representing a joint distribution as univariate margins plus copulas allows the separationMoving-average model (749 words) [view diff] no match in snippet view article find links to article

also known as moving-average process, is a common approach for modeling univariate time series. The moving-average model specifies that the output variableBeta-binomial distribution (3,072 words) [view diff] no match in snippet view article find links to article

Dirichlet-multinomial distribution as the binomial and beta distributions are univariate versions of the multinomial and Dirichlet distributions respectively.Wallenius' noncentral hypergeometric distribution (1,875 words) [view diff] no match in snippet view article find links to article

; n , m , N ) {\displaystyle \operatorname {hypg} (x;n,m,N)} is the (univariate, central) hypergeometric distribution probability. The balls that areCharacteristic function (probability theory) (4,854 words) [view diff] no match in snippet view article

distributions defined by the weighted sums of random variables. In addition to univariate distributions, characteristic functions can be defined for vector or matrix-valuedMultivariate Pareto distribution (1,461 words) [view diff] no match in snippet view article find links to article

In statistics, a multivariate Pareto distribution is a multivariate extension of a univariate Pareto distribution. There are several different types ofStatPlus (157 words) [view diff] no match in snippet view article find links to article

basic univariate and multivariate statistical analysis (MANOVA, GLM, Latin squares), as well as time series analysis, nonparametric statistics, survivalGeneralized randomized block design (1,237 words) [view diff] no match in snippet view article find links to article

to experimental units. When Mandel's multiplicative model holds, the F-statistics randomization distribution is closely approximated by the distributionMoment-generating function (2,422 words) [view diff] no match in snippet view article find links to article

moment-generating function, evaluated at 0. In addition to real-valued distributions (univariate distributions), moment-generating functions can be defined for vector-Moment-generating function (2,422 words) [view diff] no match in snippet view article find links to article

moment-generating function, evaluated at 0. In addition to real-valued distributions (univariate distributions), moment-generating functions can be defined for vector-Economic data (1,500 words) [view diff] no match in snippet view article find links to article

regression, Box–Jenkins analysis, and seasonality analysis. Analysis may be univariate (modeling one series) or multivariate (from several series). EconometriciansMultivariate Behrens–Fisher problem (1,766 words) [view diff] no match in snippet view article find links to article

a generalization of the univariate Behrens-Fisher problem, it inherits all of the difficulties that arise in the univariate problem. Let X i j ∼ N pVector autoregression (3,328 words) [view diff] no match in snippet view article find links to article

interdependencies among multiple time series. VAR models generalize the univariate autoregressive model (AR model) by allowing for more than one evolvingEstimation of distribution algorithm (4,012 words) [view diff] no match in snippet view article find links to article

univariate EDAs rely only on univariate statistics and multivariate distributions must be factorized as the product of N {\displaystyle N} univariateHalf-logistic distribution (246 words) [view diff] no match in snippet view article find links to article

Johnson, N. L.; Kotz, S.; Balakrishnan, N. (1994). "23.11". Continuous univariate distributions. 2 (2nd ed.). New York: Wiley. p. 150. George, Olusegun;Mean absolute difference (1,451 words) [view diff] no match in snippet view article find links to article

The mean absolute difference (univariate) is a measure of statistical dispersion equal to the average absolute difference of two independent values drawnFisher's noncentral hypergeometric distribution (2,371 words) [view diff] no match in snippet view article find links to article

called "finchy-pig," based on the abbreviation convention above. The univariate noncentral hypergeometric distribution may be derived alternatively asMaximum spacing estimation (3,312 words) [view diff] no match in snippet view article find links to article

spacing estimation (MPS), is a method for estimating the parameters of a univariate statistical model. The method requires maximization of the geometric meanSlice sampling (2,572 words) [view diff] no match in snippet view article find links to article

value from the distribution as done in Gibbs. This method adapts the univariate algorithm to the multivariate case by substituting a hyperrectangle forKurtosis (4,356 words) [view diff] no match in snippet view article find links to article

and not the configuration of data near the mean. The kurtosis of any univariate normal distribution is 3. It is common to compare the kurtosis of a distributionCompound probability distribution (1,755 words) [view diff] no match in snippet view article find links to article

Introduction to the theory of statistics (3rd ed.). New York: McGraw-Hill. Johnson, N. L.; Kemp, A. W.; Kotz, S. (2005). "6.2.2". Univariate discrete distributionsBernoulli distribution (1,481 words) [view diff] no match in snippet view article find links to article

(1993). Univariate Discrete Distributions (2nd ed.). Wiley. ISBN 0-471-54897-9. Peatman, John G. (1963). Introduction to Applied Statistics. New York:Kernel density estimation (4,443 words) [view diff] no match in snippet view article find links to article

independently creating it in its current form. Let (x1, x2, …, xn) be a univariate independent and identically distributed sample drawn from some distributionRelationships among probability distributions (2,270 words) [view diff] no match in snippet view article find links to article

Computational Statistics. 594 (2): 249–271. doi:10.1007/s00180-015-0594-6. PMC 4856044. PMID 27158191. Interactive graphic: Univariate Distribution RelationshipsRobust statistics (5,652 words) [view diff] no match in snippet view article find links to article

way that they mask each other. As a simple example, consider a small univariate data set containing one modest and one large outlier. The estimated standardStatistical model (2,180 words) [view diff] no match in snippet view article find links to article

dimension of the model. As an example, if we assume that data arise from a univariate Gaussian distribution, then we are assuming that P = { P μ , σ ( x ) ≡Hyperbolic secant distribution (597 words) [view diff] no match in snippet view article find links to article

Johnson, Norman L.; Kotz, Samuel; Balakrishnan, N. (1995). Continuous Univariate Distributions. 2. ISBN 978-0-471-58494-0. Ding, P. (2014). "Three occurrencesExtended negative binomial distribution (595 words) [view diff] no match in snippet view article find links to article

}}|s|\leq {\frac {1}{p}}.} Jonhnson, N.L.; Kotz, S.; Kemp, A.W. (1993) Univariate Discrete Distributions, 2nd edition, Wiley ISBN 0-471-54897-9 (page 227)Nonparametric regression (428 words) [view diff] no match in snippet view article find links to article

predicting univariate data, the framework can be used to predict multivariate data, including time series. Local regression Non-parametric statistics SemiparametricGeneralized additive model (5,576 words) [view diff] no match in snippet view article find links to article

of generalized linear models with additive models. The model relates a univariate response variable, Y, to some predictor variables, xi. An exponentialStatistical graphics (648 words) [view diff] no match in snippet view article find links to article

for Univariate and Bivariate Data: Statistical Graphics pp.2–4 James R. Beniger and Dorothy L. Robyn (1978). "Quantitative graphics in statistics: A briefSamarendra Nath Roy (1,096 words) [view diff] no match in snippet view article find links to article

contributions to the theory of univariate and multivariate statistical analysis". Sources: Fellow of the Institute of Mathematical Statistics Fellow of the InternationalList of statistical software (1,407 words) [view diff] no match in snippet view article find links to article

similar to WinBUGS JMulTi – For econometric analysis, specialised in univariate and multivariate time series analysis KNIME - An open source analyticsM-estimator (2,563 words) [view diff] no match in snippet view article find links to article

median as an estimate of location and the median absolute deviation as a univariate estimate of scale, are common. In computation of M-estimators, it is sometimesShapiro–Wilk test (799 words) [view diff] no match in snippet view article find links to article

and Shapiro–Francia tests for normality Park, Hun Myoung (2002–2008). "Univariate Analysis and Normality Test Using SAS, Stata, and SPSS" (PDF). [workingT distribution (24 words) [view diff] no match in snippet view article find links to article

Student's t-distribution in univariate probability theory, Hotelling's T-square distribution in multivariate statistics. Multivariate Student distributionCredit analysis (883 words) [view diff] no match in snippet view article find links to article

objective, quantitative systems for scoring credits have been developed. In univariate (one variable) accounting-based credit-scoring systems, the credit analystSplit normal distribution (1,331 words) [view diff] no match in snippet view article find links to article

Villani and Larsson. They assume that each of the principal components has univariate split normal distribution with a different set of parameters μ, σ2 andDot plot (statistics) (485 words) [view diff] no match in snippet view article

plotted on a simple scale. Dot plots are used for continuous, quantitative, univariate data. Data points may be labelled if there are few of them. Dot plotsFrequency distribution (828 words) [view diff] no match in snippet view article find links to article

values within a particular group or interval. Here is an example of a univariate (single variable) frequency table. The frequency of each response to aGoldfeld–Quandt test (968 words) [view diff] no match in snippet view article find links to article

associated only with the former. In the context of multiple regression (or univariate regression), the hypothesis to be tested is that the variances of thePoisson distribution (10,049 words) [view diff] no match in snippet view article find links to article

Poisson distribution can be deduced from the limiting distribution of univariate multinomial distribution. It is also a special case of a compound PoissonAutoregressive–moving-average model (2,230 words) [view diff] no match in snippet view article find links to article

library of numerical methods, including comprehensive statistics packages, in which univariate/multivariate ARMA, ARIMA, ARMAX, etc. models are implementedInverse-Wishart distribution (2,787 words) [view diff] no match in snippet view article find links to article

A univariate specialization of the inverse-Wishart distribution is the inverse-gamma distribution. With p = 1 {\displaystyle p=1} (i.e. univariate) andBates distribution (626 words) [view diff] no match in snippet view article find links to article

distribution Jonhson, N. L.; Kotz, S.; Balakrishnan (1995) Continuous Univariate Distributions, Volume 2, 2nd Edition, Wiley ISBN 0-471-58494-0(SectionMultilevel model (3,207 words) [view diff] no match in snippet view article find links to article

As such, multilevel models provide an alternative type of analysis for univariate or multivariate analysis of repeated measures. Individual differencesMixture distribution (2,794 words) [view diff] no match in snippet view article find links to article

normal mixture are explored by Ray & Lindsay extending the earlier work on univariate and multivariate distributions (Carreira-Perpinan and Williams, 2003)Normality test (1,518 words) [view diff] no match in snippet view article find links to article

grasp that "6σ events are very rare in normal distributions". Tests of univariate normality include the following: D'Agostino's K-squared test, Jarque–BeraProbOnto (2,001 words) [view diff] no match in snippet view article find links to article

re-parameterization formulas, supporting also the encoding of empirical and univariate mixture distributions. ProbOnto was initially designed to facilitate theLogarithmic distribution (373 words) [view diff] no match in snippet view article find links to article

Samuel (2005). "Chapter 7: Logarithmic and Lagrangian distributions". Univariate discrete distributions (3 ed.). John Wiley & Sons. ISBN 978-0-471-27246-5Generalized extreme value distribution (2,396 words) [view diff] no match in snippet view article find links to article

reversed Weibull has an upper limit. More precisely, Extreme Value Theory (Univariate Theory) describes which of the three is the limiting law according toCopula (probability theory) (6,394 words) [view diff] no match in snippet view article

states that any multivariate joint distribution can be written in terms of univariate marginal distribution functions and a copula which describes the dependenceCauchy distribution (5,631 words) [view diff] no match in snippet view article find links to article

(1994). Continuous Univariate Distributions, Volume 1. New York: Wiley., Chapter 16. Cauchy and the Witch of Agnesi in Statistics on the Table, S M StiglerMultivariate analysis (653 words) [view diff] no match in snippet view article find links to article

independent modelling of class analogies (SIMCA) Statistical interference Univariate analysis Olkin, I.; Sampson, A. R. (2001-01-01), "Multivariate Analysis:Delaporte distribution (471 words) [view diff] no match in snippet view article find links to article

ISBN 978-0-470-01250-5. Johnson, Norman Lloyd; Kemp, Adrienne W.; Kotz, Samuel (2005). Univariate discrete distributions (Third ed.). John Wiley & Sons. pp. 241–242.List of statistics articles (8,295 words) [view diff] no match in snippet view article find links to article

Unit (statistics) Unit of observation Unit root Unit root test Unit-weighted regression Unitized risk Univariate Univariate analysis Univariate distributionMarginal model (273 words) [view diff] no match in snippet view article find links to article

marginalize (see also conditional probability) the joint distribution into a univariate normal distribution. We then fit the marginal model to data. For exampleWeibull distribution (4,127 words) [view diff] no match in snippet view article find links to article

Continuous univariate distributions. Vol. 1, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics (2nd ed.), NewWeibull distribution (4,127 words) [view diff] no match in snippet view article find links to article

Continuous univariate distributions. Vol. 1, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics (2nd ed.), NewIrwin–Hall distribution (1,093 words) [view diff] no match in snippet view article find links to article

distribution Johnson, N.L.; Kotz, S.; Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, 2nd Edition, Wiley ISBN 0-471-58494-0(SectionMauchly's sphericity test (1,501 words) [view diff] no match in snippet view article find links to article

violated, a decision must be made as to whether a univariate or multivariate analysis is selected. If a univariate method is selected, the repeated-measures ANOVAGeneralized logistic distribution (630 words) [view diff] no match in snippet view article find links to article

distribution. Johnson, N.L., Kotz, S., Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, Wiley. ISBN 0-471-58494-0 (pages 140–142)Growth curve (statistics) (736 words) [view diff] no match in snippet view article

(Chapter 7)". Univariate and multivariate general linear models: Theory and applications with SAS (with 1 CD-ROM for Windows and UNIX). Statistics: TextbooksGeostatistics (1,809 words) [view diff] no match in snippet view article find links to article

other areas of spatial statistics. D-STEM is a software based on the MATLAB language able to handle spatiotemporal univariate and multivariate datasetsGamma/Gompertz distribution (584 words) [view diff] no match in snippet view article find links to article

Johnson, Norman L.; Kotz, Samuel; Balakrishnan, N. (1995). "Continuous Univariate Distributions". 2 (2nd ed.). New York: John Wiley & Sons: 25–26. ISBN 0-471-58494-0Logistic distribution (1,565 words) [view diff] no match in snippet view article find links to article

ISBN 0-8247-8587-8. Johnson, N. L.; Kotz, S.; N., Balakrishnan (1995). Continuous Univariate Distributions. Vol. 2 (2nd ed.). ISBN 0-471-58494-0. Modis, Theodore (1992)Akaike information criterion (5,359 words) [view diff] no match in snippet view article find links to article

for AICc depends upon the statistical model. Assuming that the model is univariate, is linear in its parameters, and has normally-distributed residuals (conditionalThurstonian model (1,435 words) [view diff] no match in snippet view article find links to article

form for ranking tasks is presented that only involves the product of univariate normal distribution functions and includes rank-induced dependency parametersData transformation (statistics) (2,731 words) [view diff] no match in snippet view article

transformation is to address the problem of lack of normality in error terms. Univariate normality is not needed for least squares estimates of the regressionNoncentral chi-squared distribution (3,109 words) [view diff] no match in snippet view article find links to article

distribution", Biometrika 46, 235–237 Johnson et al. (1995) Continuous Univariate Distributions Section 29.8 Muirhead (2005) pages 22–24 and problem 1.18Location parameter (839 words) [view diff] no match in snippet view article find links to article

distribution is therefore part of a location family. For the continuous univariate case, consider a probability density function f ( x | θ ) , x ∈ [ a ,Location–scale family (718 words) [view diff] no match in snippet view article find links to article

members have the same functional form. Most location–scale families are univariate, though not all. Well-known families in which the functional form of theProbability mass function (1,560 words) [view diff] no match in snippet view article find links to article

multiple names: authors list (link) Johnson, N. L.; Kotz, S.; Kemp, A. (1993). Univariate Discrete Distributions (2nd ed.). Wiley. p. 36. ISBN 0-471-54897-9.Minimum-variance unbiased estimator (1,073 words) [view diff] no match in snippet view article find links to article

Theoretical Statistics. Springer. pp. 47–48, 57–58. Voinov V. G., Nikulin M.S. (1993). Unbiased estimators and their applications, Vol.1: Univariate case. KluwerTaguchi methods (2,668 words) [view diff] no match in snippet view article find links to article

allowing) to explore possible high-order univariate effects of the remaining variables, as high-order univariate effects are less likely in variables alreadyCorrelogram (1,213 words) [view diff] no match in snippet view article find links to article

this formula are of no value unless the randomness assumption holds. For univariate data, the default model is Y = constant + error {\displaystyleMahalanobis distance (1,821 words) [view diff] no match in snippet view article find links to article

distributions, a point can be a multivariate outlier even if it is not a univariate outlier for any variable (consider a probability density concentratedBias of an estimator (5,291 words) [view diff] no match in snippet view article find links to article

Laplace. Other loss functions are used in statistics, particularly in robust statistics. As stated above, for univariate parameters, median-unbiased estimatorsMedcouple (3,528 words) [view diff] no match in snippet view article find links to article

In statistics, the medcouple is a robust statistic that measures the skewness of a univariate distribution. It is defined as a scaled median differenceGeneralized inverse Gaussian distribution (1,149 words) [view diff] no match in snippet view article find links to article

Continuous univariate distributions. Vol. 1, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics (2nd ed.), NewAP Statistics (1,924 words) [view diff] no match in snippet view article find links to article

and numerical techniques to analyze distributions of data, including univariate, bivariate, and categorical data. The second theme involves planning andLomax distribution (782 words) [view diff] no match in snippet view article find links to article

Kotz, S.; Balakrishnan, N. (1994). "20 Pareto distributions". Continuous univariate distributions. 1 (2nd ed.). New York: Wiley. p. 573. J. Chen, J., AddieChebyshev's inequality (11,318 words) [view diff] no match in snippet view article find links to article

^{2})}{N^{2}\lambda ^{2}}}\right\rfloor \right\}.\end{aligned}}} In the univariate case, i.e. n ξ = 1 {\textstyle n_{\xi }=1} , this inequality correspondsScore test (1,546 words) [view diff] no match in snippet view article find links to article

Let L {\displaystyle L} be the likelihood function which depends on a univariate parameter θ {\displaystyle \theta } and let x {\displaystyle x} be theGeneralized beta distribution (3,865 words) [view diff] no match in snippet view article find links to article

;c\\p+q+t\sigma ;\end{bmatrix}}.} A multivariate generalized beta pdf extends the univariate distributions listed above. For n {\displaystyle n} variables y = ( yF-distribution (2,099 words) [view diff] no match in snippet view article find links to article

Johnson, Norman Lloyd; Samuel Kotz; N. Balakrishnan (1995). Continuous Univariate Distributions, Volume 2 (Second Edition, Section 27). Wiley. ISBN 0-471-58494-0Complex normal distribution (2,336 words) [view diff] no match in snippet view article find links to article

relation matrix C {\displaystyle C} . The standard complex normal is the univariate distribution with μ = 0 {\displaystyle \mu =0} , Γ = 1 {\displaystyleMinimum mean square error (7,671 words) [view diff] no match in snippet view article find links to article

In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE),Plot (graphics) (2,530 words) [view diff] no match in snippet view article

plotted on a simple scale. Dot plots are used for continuous, quantitative, univariate data. Data points may be labelled if there are few of them. Dot plotsBinomial distribution (6,752 words) [view diff] no match in snippet view article find links to article

Generation, New York: Springer-Verlag. (See especially Chapter X, Discrete Univariate Distributions) Kachitvichyanukul, V.; Schmeiser, B. W. (1988). "BinomialCalibration (statistics) (1,086 words) [view diff] no match in snippet view article

multi-class classification tasks is given by Gebel (2009) . The following univariate calibration methods exist for transforming classifier scores into classProbabilistic classification (917 words) [view diff] no match in snippet view article find links to article

multiclass case, one can use a reduction to binary tasks, followed by univariate calibration with an algorithm as described above and further application2011 United Kingdom census (6,587 words) [view diff] no match in snippet view article find links to article

Statistics – KS (same as in 2001) Quick Statistics – QS (formerly Univariate (UV) tables) Local Characteristics – LC (formerly Census Area StatisticsGreenbook (696 words) [view diff] no match in snippet view article find links to article

Research paper by Faust and Wright finds: "For inflation we find that univariate methods are dominated by the best atheoretical large dataset methods andInfinite divisibility (probability) (830 words) [view diff] no match in snippet view article

ISBN 978-0-521-55302-5. Johnson, N.L., Kotz, S., Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, 2nd Edition. Wiley, ISBN 0-471-58494-0 (ChapterGompertz distribution (1,293 words) [view diff] no match in snippet view article find links to article

Johnson, Norman L.; Kotz, Samuel; Balakrishnan, N. (1995). Continuous Univariate Distributions. 2 (2nd ed.). New York: John Wiley & Sons. pp. 25–26. ISBN 0-471-58494-0Spearman's rank correlation coefficient (2,443 words) [view diff] no match in snippet view article find links to article

correlation Scale types. Lehman, Ann (2005). Jmp For Basic Univariate And Multivariate Statistics: A Step-by-step Guide. Cary, NC: SAS Press. p. 123. ISBN 978-1-59047-576-8Heteroscedasticity (2,660 words) [view diff] no match in snippet view article find links to article

for heteroscedasticity between grouped data, used most commonly in the univariate case, has also been extended for the multivariate case, but a tractableWorld Programming System (956 words) [view diff] no match in snippet view article find links to article

STDSIZE, STEPDISC, SUMMARY, SURVEYSELECT, TPSPLINE, TRANSREG, TREE, TTEST, UNIVARIATE, VARCLUS, VARCOMP Support for time series procedures ARIMA, AUTOREG, EXPANDQuadratic equation (6,230 words) [view diff] no match in snippet view article find links to article

Because the quadratic equation involves only one unknown, it is called "univariate". The quadratic equation only contains powers of x that are non-negativeHistogram (3,017 words) [view diff] no match in snippet view article find links to article

Modern Applied Statistics with S (2002), Springer, 4th edition. ISBN 0-387-95457-0. "EXCEL Univariate: Histogram". Online Statistics Education: A MultimediaEstimation theory (2,611 words) [view diff] no match in snippet view article find links to article

Voinov, M.S.Nikulin, "Unbiased estimators and their applications. Vol.1: Univariate case", Kluwer Academic Publishers, 1993, ISBN 0-7923-2382-3. V.G.VoinovSkewness (3,854 words) [view diff] no match in snippet view article find links to article

and Graphical Statistics. 13 (4): 996–1017. doi:10.1198/106186004X12632. Johnson, NL, Kotz, S, Balakrishnan N (1994) Continuous Univariate DistributionsLaplace distribution (2,344 words) [view diff] no match in snippet view article find links to article

Cambridge Dictionary of Statistics, CUP. ISBN 0-521-81099-X Johnson, N.L., Kotz S., Balakrishnan, N. (1994) Continuous Univariate Distributions, Wiley.Projection pursuit regression (1,808 words) [view diff] no match in snippet view article find links to article

It uses univariate regression functions instead of their multivariate form, thus effectively dealing with the curse of dimensionality Univariate regressionHerman Wold (1,085 words) [view diff] no match in snippet view article find links to article

Russian mathematicians, principally A. Ya. Khinchin. Wold's results on univariate time series were generalized to multivariate time series by his studentStudentized residual (1,530 words) [view diff] no match in snippet view article find links to article

residual distributions at different data points, unlike point estimators of univariate distributions, which share a common distribution for residuals. For thisLog-normal distribution (7,907 words) [view diff] no match in snippet view article find links to article

Granger-cause y, one first finds the proper lagged values of y to include in a univariate autoregression of y: y t = a 0 + a 1 y t − 1 + a 2 y t − 2 + ⋯ + a m yImputation (statistics) (1,998 words) [view diff] no match in snippet view article

measured variables. Thus, mean imputation has some attractive properties for univariate analysis but becomes problematic for multivariate analysis. RegressionGeometric Poisson distribution (419 words) [view diff] no match in snippet view article find links to article

p. 412. Özel & İnal 2010. Johnson, N.L.; Kotz, S.; Kemp, A.W. (2005). Univariate Discrete Distributions (3rd ed.). New York: Wiley. Nuel, Grégory (MarchBox–Behnken design (601 words) [view diff] no match in snippet view article find links to article

points", as in central composite designs, but, in this case, to estimate univariate cubic and quartic effects, with length α = min(2, (int(1.5 + K/4))1/2)Pao-Lu Hsu (1,161 words) [view diff] no match in snippet view article find links to article

obtains the first optimum property for the likelihood ratio test of the univariate linear hypothesis, in fact essentially the first nonlocal optimum propertyStudent's t-test (4,964 words) [view diff] no match in snippet view article find links to article

usually positively correlated, it is not advisable to conduct separate univariate t-tests to test hypotheses, as these would neglect the covariance amongGeneralized Pareto distribution (2,385 words) [view diff] no match in snippet view article find links to article

in Statistics - Theory and Methods. 0: 1–25. doi:10.1080/03610926.2018.1441418. N. L. Johnson; S. Kotz; N. Balakrishnan (1994). Continuous Univariate DistributionsBirnbaum–Saunders distribution (1,123 words) [view diff] no match in snippet view article find links to article

Journal of Statistics, 13 (3): 171–183, doi:10.2307/3315148, JSTOR 3315148 Johnson, N.; Kotz, S.; Balakrishnan, N. (1995), Continuous Univariate DistributionsRegression analysis (5,040 words) [view diff] no match in snippet view article find links to article

convenient form for f {\displaystyle f} is chosen. For example, a simple univariate regression may propose f ( X i , β ) = β 0 + β 1 X i {\displaystyle f(X_{i}Zero-inflated model (990 words) [view diff] no match in snippet view article find links to article

JSTOR 1269547. Johnson, Norman L.; Kotz, Samuel; Kemp, Adrienne W. (1992). Univariate Discrete Distributions (2nd ed.). Wiley. pp. 312–314. ISBN 978-0-471-54897-3Calibration curve (1,160 words) [view diff] no match in snippet view article find links to article

ISBN 0-495-01201-7. Lavagnini I, Magno F (2007). "A statistical overview on univariate calibration, inverse regression, and detection limits: Application toWishart distribution (3,865 words) [view diff] no match in snippet view article find links to article

Seber prefers to reserve the term multivariate for the case when all univariate marginals belong to the same family. The Wishart distribution is the samplingOlympic medal table (2,308 words) [view diff] no match in snippet view article find links to article

particular ranking system. Sporting success predictions and ratings can be univariate, i.e. based on one independent variable, such as a country's populationHypoexponential distribution (1,628 words) [view diff] no match in snippet view article find links to article

Stochastic Models, 15(4), 731–757. L. Leemis and J. McQueston (2008). Univariate distribution relationships, The American Statistician, 62(1), 45—53. SMultivariate adaptive regression spline (3,299 words) [view diff] no match in snippet view article find links to article

extensions to include moving average spline models are described in "Univariate Time Series Modelling and Forecasting using TSMARS: A study of thresholdModifiable areal unit problem (1,859 words) [view diff] no match in snippet view article find links to article

ecological bias caused by spatial data aggregation. Using simulations for univariate data, Larsen advocated the use of a Variance Ratio to investigate thePeter Whittle (mathematician) (1,433 words) [view diff] no match in snippet view article

Series, generalised Wold's autoregressive representation theorem for univariate stationary processes to multivariate processes. Whittle's thesis was publishedData analysis (5,130 words) [view diff] no match in snippet view article find links to article

Several analyses can be used during the initial data analysis phase: Univariate statistics (single variable) Bivariate associations (correlations) GraphicalStandard deviation (7,981 words) [view diff] no match in snippet view article find links to article

square root of the average value of (X − μ)2. The standard deviation of a (univariate) probability distribution is the same as that of a random variable havingBeta prime distribution (1,369 words) [view diff] no match in snippet view article find links to article

1007/BF02613934. Johnson, N.L., Kotz, S., Balakrishnan, N. (1995). Continuous Univariate Distributions, Volume 2 (2nd Edition), Wiley. ISBN 0-471-58494-0 MathWorldBootstrapping (statistics) (6,786 words) [view diff] no match in snippet view article

not heavy tailed, one should hesitate to use the naive bootstrap". In univariate problems, it is usually acceptable to resample the individual observationsColegio San José (San Juan, Puerto Rico) (978 words) [view diff] no match in snippet view article

Writing, and Forensics Advanced Placement (AP) Univariate Calculus Advanced Placement (AP) Univariate Statistics Advanced Physics or Chemistry Advanced AnatomyF-test of equality of variances (827 words) [view diff] no match in snippet view article find links to article

University Press. Johnson, N.L., Kotz, S., Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 2, Wiley. ISBN 0-471-58494-0 (Section 27.1) BoxAutocorrelation (5,234 words) [view diff] no match in snippet view article find links to article

Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques. Cambridge University Press. pp. 190–195. ISBN 978-0-521-43541-3Holtsmark distribution (1,476 words) [view diff] no match in snippet view article find links to article

ISBN 978-0-8218-4519-6. holtsmark. Nolan, J. P. (2008). "Basic Properties of Univariate Stable Distributions" (PDF). Stable Distributions: Models for Heavy TailedBayesian multivariate linear regression (2,690 words) [view diff] no match in snippet view article find links to article

likelihood and then find the appropriate conjugate prior. As with the univariate case of linear Bayesian regression, we will find that we can specify aSexual dimorphism measures (2,586 words) [view diff] no match in snippet view article find links to article

A.I. (2000) A measure of sexual dimorphism in populations which are univariate normal mixtures. Bull. Math. Biol. 62: 925-941. Ipiña, S.L. and DurandPareto distribution (5,232 words) [view diff] no match in snippet view article find links to article

Kotz S, Balakrishnan N (1994) Continuous univariate distributions Vol 1. Wiley Series in Probability and Statistics. Johnson, Kotz, and Balakrishnan (1994)Chi-squared distribution (5,594 words) [view diff] no match in snippet view article find links to article

(1994). "Chi-Square Distributions including Chi and Rayleigh". Continuous Univariate Distributions. 1 (Second ed.). John Wiley and Sons. pp. 415–493. ISBN 978-0-471-58495-7Further Mathematics (1,044 words) [view diff] no match in snippet view article find links to article

usually by the school or teacher) from a list of four. The core modules are Univariate Data, Bivariate Data, Time Series, Number Patterns and Business-RelatedOptimal discriminant analysis and classification tree analysis (477 words) [view diff] no match in snippet view article find links to article

AU - Soltysik, Robert C. TI - Theoretical Distributions of Optima for Univariate Discrimination of Random Data* JO - Decision Sciences VL - 22 IS - 4 PBMixture model (7,783 words) [view diff] no match in snippet view article find links to article

used to generate multivariate tail-dependencies consistent with a set of univariate and (in some sense) bivariate moments. The performance of this methodGeometric median (2,428 words) [view diff] no match in snippet view article find links to article

the geometric median coincides with the median. This is because the univariate median also minimizes the sum of distances from the points. The geometricHarmonic mean (5,543 words) [view diff] no match in snippet view article find links to article

Kotz S, Balakrishnan N (1994) Continuous univariate distributions Vol 1. Wiley Series in Probability and Statistics. Zelen M (1972) Length-biased samplingAlfred Aeppli (332 words) [view diff] no match in snippet view article find links to article

Naval Research Logistics Quarterly. 15: 189–203. Johnson, N.L.; Kotz, S.; Kemp, A.W. (2005). Univariate Discrete Distributions (3rd ed.). New York: Wiley.Zipf's law (2,990 words) [view diff] no match in snippet view article find links to article

Applied Statistics. 42 (12): 2686–2693. arXiv:1506.08535. doi:10.1080/02664763.2015.1047744. N. L. Johnson; S. Kotz & A. W. Kemp (1992). Univariate DiscreteAutoregressive integrated moving average (2,998 words) [view diff] no match in snippet view article find links to article

series analysis – univariate time series analysis: AR, ARIMA – vector autoregressive models, VAR and structural VAR – descriptive statistics and process modelsTruncated distribution (1,474 words) [view diff] no match in snippet view article find links to article

ISBN 0-19-920613-9 Johnson, N.L., Kotz, S., Balakrishnan, N. (1994) Continuous Univariate Distributions, Volume 1, Wiley. ISBN 0-471-58495-9 (Section 10.1)Inverse distribution (1,345 words) [view diff] no match in snippet view article find links to article

Norman L.; Kotz, Samuel; Balakrishnan, Narayanaswamy (1994). Continuous Univariate Distributions, Volume 1. Wiley. p. 171. ISBN 0-471-58495-9. Hayya, Jack;Paris Institute of Statistics (684 words) [view diff] no match in snippet view article find links to article

Analysis 'Univariate and multivariate' Statistics Software SAS Economics Stochastic processes Linear regression models Econometrics Inferential statistics CorporateGaussian process (4,365 words) [view diff] no match in snippet view article find links to article

t 1 , … , X t k ) {\displaystyle (X_{t_{1}},\ldots ,X_{t_{k}})} has a univariate normal (or Gaussian) distribution. Using characteristic functions of randomCompound Poisson distribution (2,059 words) [view diff] no match in snippet view article find links to article

functions. London: Griffin. Johnson, N.L., Kemp, A.W., and Kotz, S. (2005) Univariate Discrete Distributions, 3rd Edition, Wiley, ISBN 978-0-471-27246-5. HuimingCentral limit theorem (8,280 words) [view diff] no match in snippet view article find links to article

k-vector. The bold in Xi means that it is a random vector, not a random (univariate) variable. Then the sum of the random vectors will be [ X 1 ( 1 ) ⋮ XDe-sparsified lasso (629 words) [view diff] no match in snippet view article find links to article

covariables x i ∈ χ ⊂ R p {\displaystyle x_{i}\in \chi \subset R^{p}} and univariate responses y i ∈ Y ⊂ R {\displaystyle y_{i}\in Y\subset R} for i = 1 ,Michael Akritas (523 words) [view diff] no match in snippet view article find links to article

1032–1038. Akritas, M.G. (1988). Pearson-Type Goodness-of-Fit Tests: The Univariate Case. J. Amer. Statist. Assoc. 83, 222–230. Akritas, M.G. (1990). TheReduced chi-squared statistic (1,788 words) [view diff] no match in snippet view article find links to article

usage in isotopic dating. In general when: MSWD = 1 if the age data fit a univariate normal distribution in t (for the arithmetic mean age) or log(t) (forKarl Pearson (5,956 words) [view diff] no match in snippet view article find links to article

descriptive statistics and for the fitting of distributions to samples. Pearson's system of continuous curves. A system of continuous univariate probabilityPrincipal component regression (5,089 words) [view diff] no match in snippet view article find links to article

carrying out k {\displaystyle k} independent simple linear regressions (or univariate regressions) separately on each of the k {\displaystyle k} selected principalMultitaper (1,204 words) [view diff] no match in snippet view article find links to article

Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques. Cambridge: Cambridge University Press, 1993. Slepian, D. (1978)Coordinate descent (1,571 words) [view diff] no match in snippet view article find links to article

achieved by minimizing it along one direction at a time, i.e., solving univariate (or at least much simpler) optimization problems in a loop. In the simplestRaymond Cattell (8,259 words) [view diff] no match in snippet view article find links to article

psychological aspect especially personality aspect. Rather than pursue a "univariate" research approach to psychology, studying the effect that a single variableMETAGENassist (720 words) [view diff] no match in snippet view article find links to article

normalization. METAGENassist also supports an extensive collection of classical univariate and multivariate analyses, such as fold-change analysis, t-tests, one-wayTilapia (3,821 words) [view diff] no match in snippet view article find links to article

Rajesh (2019-08-05). "Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)".Student's t-distribution (7,527 words) [view diff] no match in snippet view article find links to article

Johnson NL, Kotz S, Balakrishnan N (1995). "Chapter 28". Continuous Univariate Distributions. 2 (2nd ed.). Wiley. ISBN 9780471584940. Gelman AB, CarlinMaximum likelihood estimation (9,362 words) [view diff] no match in snippet view article find links to article

) {\displaystyle f_{n}(\mathbf {y} ;\theta )} will be the product of univariate density functions. The goal of maximum likelihood estimation is to findGeneralized functional linear model (2,868 words) [view diff] no match in snippet view article find links to article

extension of the generalized linear model (GLM) that allows one to regress univariate responses of various types (continuous or discrete) on functional predictorsGeneralized gamma distribution (918 words) [view diff] no match in snippet view article find links to article

Annals of Mathematical Statistics 33(3): 1187-1192. JSTOR 2237889 Johnson, N.L.; Kotz, S; Balakrishnan, N. (1994) Continuous Univariate Distributions, VolumeStochastic volatility (2,045 words) [view diff] no match in snippet view article find links to article

University Press. p. 461. ISBN 9781107661455. Ghalanos, Alexios. "rugarch: Univariate GARCH models". Ardia, David; Hoogerheide, Lennart F. (2010). "BayesianConvex hull (6,093 words) [view diff] no match in snippet view article find links to article

are used in a standard definition of the home range. Newton polygons of univariate polynomials and Newton polytopes of multivariate polynomials are convexDirichlet distribution (5,853 words) [view diff] no match in snippet view article find links to article

when scale and rate equal 1.0. A less efficient algorithm relies on the univariate marginal and conditional distributions being beta and proceeds as followsMultimodal distribution (6,068 words) [view diff] no match in snippet view article find links to article

RP (1979). "An algorithm for assessing bimodality vs. unimodality in a univariate distribution". Behavior Research Methods & Instrumentation. 11 (4): 467–468Propagation of uncertainty (3,149 words) [view diff] no match in snippet view article find links to article

(1994). Continuous Univariate Distributions, Volume 1. Wiley. p. 171. ISBN 0-471-58495-9. Lecomte, Christophe (May 2013). "Exact statistics of systems withLinear predictor function (2,210 words) [view diff] no match in snippet view article find links to article

There is no particular need for the inputs to basis functions to be univariate or single-dimensional (or their outputs, for that matter, although inPERT distribution (652 words) [view diff] no match in snippet view article find links to article

distribution". Vose Software. 2017-05-02. Retrieved 2017-07-16. Continuous Univariate Distributions - 2nd Ed (1995). Johnson K, Kotz S and Balakkrishnan N.Heavy-tailed distribution (2,595 words) [view diff] no match in snippet view article find links to article

1023/A:1010012224103. Markovich N.M. (2007). Nonparametric Analysis of Univariate Heavy-Tailed data: Research and Practice. Chitester: Wiley. ISBN 978-0-470-72359-3Newton's method in optimization (2,775 words) [view diff] no match in snippet view article find links to article

optimization is minimization of functions. Let us first consider the case of univariate functions, i.e., functions of a single real variable. We will later considerGlossary of calculus (10,695 words) [view diff] no match in snippet view article find links to article

is a quadratic equation. The solutions to the univariate equation are called the roots of the univariate function. The bivariate case in terms of variablesFan chart (time series) (836 words) [view diff] no match in snippet view article

2011-03-11. Kotz, S. Johnson, M. and N. Balakrishnan (1994). Continuous univariate distributions. 1. John Wiley & Sons. Retrieved 11 March 2011.CS1 maint:Fang Kaitai (1,551 words) [view diff] no match in snippet view article find links to article

suggested that Fang provide a multivariate generalization and correction of a univariate result, which had been given an incomplete proof in a Russian paper. WithHodrick–Prescott filter (1,101 words) [view diff] no match in snippet view article find links to article

Hodrick-Prescott Filter" (PDF). Working Paper. Enders, Walter (2010). "Trends and Univariate Decompositions". Applied Econometric Time Series (Third ed.). New York:Singular spectrum analysis (6,752 words) [view diff] no match in snippet view article find links to article

missing data (Kondrashov and Ghil, 2006; Kondrashov et al. 2010). For a univariate time series, the SSA gap filling procedure utilizes temporal correlationsUnbiased estimation of standard deviation (2,962 words) [view diff] no match in snippet view article find links to article

Industrial Statistics 4th Ed., Irwin (1974) ISBN 0-256-01558-9, p.139 * N.L. Johnson, S. Kotz, and N. Balakrishnan, Continuous Univariate DistributionsBenford's law (6,138 words) [view diff] no match in snippet view article find links to article

1 and Benford's Law". Numberphile. Brady Haran. Interactive graphic: Univariate Distribution Relationships Referenced in S2 E15, "The Running Man" ofActuarial credentialing and exams (4,080 words) [view diff] no match in snippet view article find links to article

mathematics, economics, contingencies, demography, models, probability and statistics. Students may also gain exemptions by passing the exams of the InstituteError correction model (1,877 words) [view diff] no match in snippet view article find links to article

approach is easy to apply, there are, however numerous problems: The univariate unit root tests used in the first stage have low statistical power TheYates analysis (1,258 words) [view diff] no match in snippet view article find links to article

has been selected, the error term should follow the assumptions for a univariate measurement process. That is, the model should be validated by analyzingGauss Moutinho Cordeiro (3,728 words) [view diff] no match in snippet view article find links to article

para Análise de Dados Univariados (Regression Models for Analysis of Univariate Data). Printed by Sociedade Brasileira de Matemática (SBM), 1989. ModelosAnthropometry (3,397 words) [view diff] no match in snippet view article find links to article

automatically. Eighty landmarks were placed on each subject. More than 100 univariate measures were provided, over 60 from the scan and approximately 40 usingSpline (mathematics) (4,552 words) [view diff] no match in snippet view article

restricted sense.[citation needed] We begin by limiting our discussion to univariate polynomial case. In this case, a spline is a piecewise polynomial functionHerman K. van Dijk (782 words) [view diff] no match in snippet view article find links to article

censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussionAbraham de Moivre (2,493 words) [view diff] no match in snippet view article find links to article

doi:10.1093/biomet/16.3-4.402. Johnson, N.L., Kotz, S., Kemp, A.W. (1993) Univariate Discrete distributions (2nd edition). Wiley. ISBN 0-471-54897-9, p157K-means clustering (6,440 words) [view diff] no match in snippet view article find links to article

Lloyd's algorithm. Jenks natural breaks optimization: k-means applied to univariate data k-medians clustering uses the median in each dimension instead ofAnil K. Bera (3,827 words) [view diff] no match in snippet view article find links to article

hdl:2142/29151. Bera, Anil K.; Newbold, P. (1998). "Checks of Model Adequacy for Univariate Time Series Models and Their Applications to Econometric Relationships:Sensitivity analysis (7,893 words) [view diff] no match in snippet view article find links to article

outputs: Virtually all sensitivity analysis methods consider a single univariate model output, yet many models output a large number of possibly spatiallyPhilip Hans Franses (1,379 words) [view diff] no match in snippet view article find links to article

censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussionInformation-based complexity (2,338 words) [view diff] no match in snippet view article find links to article

information level and the complexity of a discrete problem is rarely known. The univariate integration problem was for illustration only. Significant for many applicationsAndrew S. C. Ehrenberg (2,003 words) [view diff] no match in snippet view article find links to article

in particular as it reduces to the simple NBD model. They labelled the univariate model as the Beta Binomial/Negative Binomial Distribution (BB/NBD). TheBeta distribution (40,031 words) [view diff] no match in snippet view article find links to article

a multivariate Beta distribution, is called a Dirichlet distribution. Univariate marginals of the Dirichlet distribution have a beta distribution. TheMutual information (7,786 words) [view diff] no match in snippet view article find links to article

understood as the expectation of the Kullback–Leibler divergence of the univariate distribution p X {\displaystyle p_{X}} of X {\displaystyle X} from theAgustín Maravall (1,538 words) [view diff] no match in snippet view article find links to article

GÓMEZ, V. and MARAVALL, A. (2001a), "Automatic Modeling Methods for Univariate Series", Ch.7 in Peña D., Tiao G.C. and Tsay, R.S. (eds.), A Course inHeritability (5,219 words) [view diff] no match in snippet view article find links to article

differences between individuals in a population. Heritability can be univariate – examining a single trait – or multivariate – examining the genetic andMulti-armed bandit (6,233 words) [view diff] no match in snippet view article find links to article

distributions of outcomes follow arbitrary (i.e., non-parametric) discrete, univariate distributions. Later in "Optimal adaptive policies for Markov decisionNoncentral hypergeometric distributions (2,340 words) [view diff] no match in snippet view article find links to article

problem Bias Biased sample Johnson, N. L.; Kemp, A. W.; Kotz, S. (2005), Univariate Discrete Distributions, Hoboken, New Jersey: Wiley and Sons. McCullaghOccupational health psychology (9,780 words) [view diff] no match in snippet view article find links to article

Quinn, R.P. et al. (1971). Survey of working conditions: Final report on univariate and bivariate tables, Document No. 2916-0001. Washington, DC: U.S. GovernmentFinancial correlation (4,196 words) [view diff] no match in snippet view article find links to article

Copulas simplify statistical problems. They allow the joining of multiple univariate distributions to a single multivariate distribution. Formally, a copulaMetabolomics (6,246 words) [view diff] no match in snippet view article find links to article

metabolomics data analysis. In the case of univariate methods, variables are analyzed one by one using classical statistics tools (such as Student's t-test, ANOVANatural selection (11,532 words) [view diff] no match in snippet view article find links to article

more than one direction. In particular, if the trait is quantitative and univariate then both higher and lower trait levels are favoured. Disruptive selectionEmery N. Brown (3,920 words) [view diff] no match in snippet view article find links to article

spiking activity and binary behavioral tasks represented as multivariate or univariate point processes (0-1 events that occur in continuous time), his researchValue at risk (5,626 words) [view diff] no match in snippet view article find links to article

ISBN 978-0995455511 Markovich, N. (2007), Nonparametric analysis of univariate heavy-tailed data, Wiley Novak, S.Y. (2011). Extreme value methods withInsurance (13,540 words) [view diff] no match in snippet view article find links to article

analyses are sometimes used when multiple characteristics are involved and a univariate analysis could produce confounded results. Other statistical methods maySpeed of light (13,718 words) [view diff] no match in snippet view article find links to article

Standards and Technology, NIST) Data Gallery: Michelson Speed of Light (Univariate Location Estimation) (download data gathered by Albert A. Michelson) SubluminalTawau (6,644 words) [view diff] no match in snippet view article find links to article

K. Assis, A. Amran, Y. Remali and H. Affendy (2010). "A Comparison of Univariate Time Series Methods for Forecasting Cocoa Bean Prices" (PDF). UniversitiHermite distribution (3,274 words) [view diff] no match in snippet view article find links to article

insmatheco.2014.09.012. Johnson, N.L., Kemp, A.W., and Kotz, S. (2005) Univariate Discrete Distributions, 3rd Edition, Wiley, ISBN 978-0-471-27246-5. KempFlow cytometry bioinformatics (7,692 words) [view diff] no match in snippet view article find links to article

analysis method in which flow cytometry data is split into quantiles on a univariate basis. The locations of the quantiles can then be used to test for differencesList of uncertainty propagation software (1,597 words) [view diff] no match in snippet view article find links to article

EDF R&D, IMACS, Phimeca). It contains state of the art algorithms for univariate, multivariate and infinite dimensional probabilistic modelling (arithmeticEberhard Voit (1,114 words) [view diff] no match in snippet view article find links to article

: The S-distribution. A tool for approximation and classification of univariate, unimodal probability distributions. ‘’Biometrical J. ‘’ ‘’’34 (7) ‘’’Medical image computing (7,953 words) [view diff] no match in snippet view article find links to article

neuroscience, computational biology, statistics, and machine learning communities. Prominent approaches include Massive univariate approaches that probe individualList of numerical analysis topics (8,294 words) [view diff] no match in snippet view article find links to article

constraints — constraints include variational inequalities or complementarities Univariate optimization: Golden section search Successive parabolic interpolationVector generalized linear model (4,737 words) [view diff] no match in snippet view article find links to article

to be generated from a particular distribution. Most distributions are univariate, so that Q 1 = 1 {\displaystyle Q_{1}=1} , and an example of Q 1 = 2 {\displaystyleGenome-wide complex trait analysis (4,461 words) [view diff] no match in snippet view article find links to article

non-additive genetics driven by frequency-dependent selection). Traits univariate GCTA has been used on (excluding SNP heritability estimates computed usingPredictive genomics (3,250 words) [view diff] no match in snippet view article find links to article

with SNPs. Currently, the prevailing standard of risk models focus on univariate analysis rather than focusing upon interactions of higher order. ThereforeProduct distribution (7,902 words) [view diff] no match in snippet view article find links to article

Johnson, Norman L.; Kotz, Samuel; Balakrishnan, N. (1995). Continuous Univariate Distributions Volume 2, Second edition. Wiley. p. 306. ISBN 978-0-471-58494-0Laplace's method (6,670 words) [view diff] no match in snippet view article find links to article

{\displaystyle |\cdot |} denotes matrix determinant. Analogously to the univariate case, the Hessian is required to be negative definite. By the way, althoughHPV-positive oropharyngeal cancer (24,013 words) [view diff] no match in snippet view article find links to article

radiation in 410 patients with a single lymph node involved, but used only univariate statistical analysis and contained no information on HPV status. A subsequent