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Longer titles found: Marginal distribution (biology) (view)

searching for Marginal distribution 57 found (102 total)

Wishart distribution (4,173 words) [view diff] exact match in snippet view article find links to article

{\displaystyle \sigma _{jj}^{-1}\,w_{jj}\sim \chi _{m}^{2}} gives the marginal distribution of each of the elements on the matrix's diagonal. George Seber points

Beta negative binomial distribution (1,537 words) [view diff] exact match in snippet view article find links to article

{\displaystyle p\sim {\textrm {B}}(\alpha ,\beta ),} then the marginal distribution of X {\displaystyle X} (i.e. the posterior predictive distribution)

Beam diameter (2,458 words) [view diff] exact match in snippet view article find links to article

three points on the marginal distribution, unlike D4σ and knife-edge widths that depend on the integral of the marginal distribution. 1/e2 width measurements

Negative multinomial distribution (1,148 words) [view diff] exact match in snippet view article find links to article

{\displaystyle q=1-\sum _{i}p_{i}^{(2)}=p_{0}+\sum _{i}p_{i}^{(1)}} The marginal distribution of X ( 1 ) {\displaystyle {\boldsymbol {X}}^{(1)}} is N M ( x 0

Estimation of distribution algorithm (4,068 words) [view diff] exact match in snippet view article find links to article

hand, quantifies the data compression in terms of entropy of the marginal distribution over all partitions, where λ {\displaystyle \lambda } is the selected

Geometric process (858 words) [view diff] exact match in snippet view article find links to article

\dots ,X_{1}=x_{1}\}=P\{X_{k}<x|X_{k-1}=x_{k-1}\}} and the marginal distribution of X k {\displaystyle X_{k}} is given by P { X k < x } = F k ( x

Normal-inverse-gamma distribution (2,039 words) [view diff] exact match in snippet view article find links to article

+1}\exp \left(-{\frac {2\beta +(x-\mu )^{2}}{2\sigma ^{2}}}\right)} Marginal distribution over x {\displaystyle x} is f ( x ∣ μ , α , β ) = ∫ 0 ∞ d σ 2 f

Ridit scoring (521 words) [view diff] exact match in snippet view article find links to article

table compares relative to an identified distribution (e.g., the marginal distribution of the dependent variable). Since ridit scoring is used to compare

Self-indication assumption doomsday argument rebuttal (3,020 words) [view diff] exact match in snippet view article find links to article

sometimes expressed in an alternative way by having the posterior marginal distribution of n based on N without explicitly invoking a non-zero chance of

Compound Poisson distribution (2,292 words) [view diff] exact match in snippet view article find links to article

obtained by combining the conditional distribution Y | N with the marginal distribution of N. The expected value and the variance of the compound distribution

UbuWeb (479 words) [view diff] exact match in snippet view article find links to article

perpetuity, in its entirety." UbuWeb was founded in response to the marginal distribution of crucial avant-garde material. It remains non-commercial and operates

Normal-inverse Gaussian distribution (905 words) [view diff] exact match in snippet view article find links to article

The normal-inverse Gaussian distribution can also be seen as the marginal distribution of the normal-inverse Gaussian process which provides an alternative

Lomax distribution (790 words) [view diff] exact match in snippet view article find links to article

Gamma(shape = k, scale = θ) and X|λ ~ Exponential(rate = λ) then the marginal distribution of X|k,θ is Lomax(shape = k, scale = 1/θ). Since the rate parameter

Matrix variate Dirichlet distribution (1,215 words) [view diff] no match in snippet view article find links to article

In statistics, the matrix variate Dirichlet distribution is a generalization of the matrix variate beta distribution and of the Dirichlet distribution

Airy process (881 words) [view diff] exact match in snippet view article find links to article

so-called extended Airy kernel. It turns out that the one-point marginal distribution of the Airy2 process is the Tracy-Widom distribution of the GUE

Multicanonical ensemble (2,157 words) [view diff] exact match in snippet view article find links to article

}P_{r}(r)\delta (f-F({\boldsymbol {r}}))\,d{\boldsymbol {r}}} is the marginal distribution of F. When the system has a large number of degrees of freedom,

Accumulated local effects (256 words) [view diff] exact match in snippet view article find links to article

and generates augmented data, creating more realistic data than a marginal distribution. It ignores far out-of-distribution (outlier) values. Unlike partial

Graph entropy (914 words) [view diff] exact match in snippet view article find links to article

{\mathcal {I}}} with the lowest mutual information such that (i) the marginal distribution of the first term is uniform and (ii) in samples from the distribution

Log-logistic distribution (2,053 words) [view diff] exact match in snippet view article find links to article

distribution with shape parameter β = 1 {\displaystyle \beta =1} is the marginal distribution of the inter-times in a geometric-distributed counting process.

Generalized least squares (2,844 words) [view diff] exact match in snippet view article find links to article

as p ( ε ) {\displaystyle p({\boldsymbol {\varepsilon }})} is a marginal distribution, it does not depend on b {\displaystyle \mathbf {b} } . Therefore

Kernel embedding of distributions (9,756 words) [view diff] exact match in snippet view article find links to article

_{\Omega }P(X,\mathrm {d} y)=} marginal distribution of X {\displaystyle X} ; P ( Y ) = {\displaystyle P(Y)=} marginal distribution of Y {\displaystyle Y} P

Inverse-Wishart distribution (3,472 words) [view diff] exact match in snippet view article find links to article

( 1 , 0 , ⋯ , 0 ) T {\displaystyle V=(1,\,0,\cdots ,0)^{T}} the marginal distribution of the leading diagonal element is thus [ A − 1 ] 1 , 1 [ Σ − 1

Exponential distribution (6,567 words) [view diff] exact match in snippet view article find links to article

If also λ ~ Gamma(k, θ) (shape, scale parametrisation) then the marginal distribution of X is Lomax(k, 1/θ), the gamma mixture λ1X1 − λ2Y2 ~ Laplace(0

Bayes estimator (3,845 words) [view diff] exact match in snippet view article find links to article

_{m}\,\!} and variance σ m {\displaystyle \sigma _{m}\,\!} of the marginal distribution of x 1 , … , x n {\displaystyle x_{1},\ldots ,x_{n}} using the maximum

Information theory (7,493 words) [view diff] exact match in snippet view article find links to article

completely determined by our channel and by our choice of f(x), the marginal distribution of messages we choose to send over the channel. Under these constraints

Empirical Bayes method (2,483 words) [view diff] exact match in snippet view article find links to article

\rho (y\mid \theta )\rho (\theta \mid \alpha ,\beta ),} where the marginal distribution has been omitted since it does not depend explicitly on θ {\displaystyle

Carl-Erik Quensel (254 words) [view diff] case mismatch in snippet view article find links to article

committee. A Method of Determining the Regression Curve When the Marginal Distribution is of the Normal Logarithmic Type, Annals of Mathematical Statistics

Markov switching multifractal (1,572 words) [view diff] exact match in snippet view article find links to article

{\displaystyle \gamma _{k}\approx \gamma _{1}b^{k-1}} at low frequency. The marginal distribution M has a unit mean, has a positive support, and is independent of

BRS-inequality (1,697 words) [view diff] exact match in snippet view article find links to article

2 , ⋯ , n {\displaystyle X_{i},i=1,2,\cdots ,n} have the same marginal distribution F {\displaystyle F} , then (6) recaptures (3), and (5) recaptures

Image segmentation (9,658 words) [view diff] exact match in snippet view article find links to article

for each label. This is termed as class statistics. Compute the marginal distribution for the given labeling scheme P(fi | ℓi) using Bayes' theorem and

Twisting properties (1,304 words) [view diff] exact match in snippet view article find links to article

Gamma parameters K and Λ {\displaystyle \Lambda } on the left. The marginal distribution of K is reported in the picture on the right. By default, capital

Jensen–Shannon divergence (2,306 words) [view diff] exact match in snippet view article find links to article

same principle to a joint distribution and the product of its two marginal distribution (in analogy to Kullback–Leibler divergence and mutual information)

Chow–Liu tree (1,341 words) [view diff] exact match in snippet view article find links to article

proof is the continuity of the mutual information in the pairwise marginal distribution. More recently, the exponential rate of convergence of the error

Von Mises–Fisher distribution (4,887 words) [view diff] exact match in snippet view article find links to article

component of x ∈ S p − 1 {\displaystyle \mathbf {x} \in S^{p-1}} . The marginal distribution for x i {\displaystyle x_{i}} has the density: f i ( x i ; p ) =

Prior probability (6,728 words) [view diff] exact match in snippet view article find links to article

joint density p ( x , t ) {\displaystyle p(x,t)} . This is the marginal distribution p ( x ) {\displaystyle p(x)} , so we have K L = ∫ p ( t ) ∫ p (

Manifold regularization (3,872 words) [view diff] exact match in snippet view article find links to article

In practice, this norm cannot be computed directly because the marginal distribution P X {\displaystyle {\mathcal {P}}_{X}} is unknown, but it can be

Gamma distribution (8,717 words) [view diff] exact match in snippet view article find links to article

{\displaystyle IG} denotes the Inverse-gamma distribution, then the marginal distribution x ∼ β ′ ( k , b ) {\displaystyle x\sim \beta '(k,b)} where β ′ {\displaystyle

Doomsday argument (6,114 words) [view diff] exact match in snippet view article find links to article

{k}{N^{2}}}\,dN} = k n . {\displaystyle ={\frac {k}{n}}.} This is why the marginal distribution of n and N are identical in the case of P(N) = k/N See, for example

Plotly (1,262 words) [view diff] exact match in snippet view article find links to article

TRUE Statistical charts Splom TRUE TRUE TRUE Statistical charts Marginal distribution plot TRUE Statistical charts Strip chart TRUE Scientific charts

Stable distribution (6,795 words) [view diff] exact match in snippet view article find links to article

Section 7 of ). Thus the stable count distribution is the first-order marginal distribution of a volatility process. In this context, ν 0 {\displaystyle \nu

Odds ratio (7,072 words) [view diff] exact match in snippet view article find links to article

they follow the correct conditional probabilities). Suppose the marginal distribution of one variable, say X, is very skewed. For example, if we are studying

Relationships among probability distributions (2,366 words) [view diff] exact match in snippet view article find links to article

distribution are random variables, the compound distribution is the marginal distribution of the variable. Examples: If X | N is a binomial (N,p) random variable

Information bottleneck method (3,658 words) [view diff] exact match in snippet view article find links to article

b)=p(a|b)p(b)=p(b|a)p(a)\,} are used. Line 3: this line finds the marginal distribution of the clusters c {\displaystyle c\,} p ( c i ) = ∑ j p ( c i ,

Pseudo-R-squared (927 words) [view diff] exact match in snippet view article find links to article

0.75 {\displaystyle R_{\text{CS}}^{2}\leq 0.75} for a symmetric marginal distribution of events and decreases further for an asymmetric distribution of

Asymptotic equipartition property (3,951 words) [view diff] exact match in snippet view article find links to article

the statistics of the process are known completely, that is, the marginal distribution of the process seen at each time instant is known. The joint distribution

Bootstrapping populations (1,253 words) [view diff] exact match in snippet view article find links to article

computed a huge set of compatible vectors, say N, the empirical marginal distribution of Θ j {\displaystyle \Theta _{j}} is obtained by: where θ ˘ j

Discrete choice (6,346 words) [view diff] exact match in snippet view article find links to article

than being independent over alternatives. Uni = βzni + εni, The marginal distribution of each εni is extreme value, but their joint distribution allows

Xiaohong Chen (1,616 words) [view diff] exact match in snippet view article find links to article

winner of the 2008 Arnold Zellner Award In the article, the unknown marginal distribution estimators and the copula dependence parameter estimators are given

Thomas Lemieux (2,186 words) [view diff] no match in snippet view article find links to article

of the explanatory variables on quantiles of the unconditional (marginal) distribution of an outcome variable. While Lemieux, Firpo and Fortin originally

Linear belief function (3,955 words) [view diff] exact match in snippet view article find links to article

corresponding to X in the above partial sweeping equation represent the marginal distribution of X in potential form. Second, according to statistics, μ 2 − μ

Information dimension (3,108 words) [view diff] exact match in snippet view article find links to article

for further compression that was not possible by considering only marginal distribution of the process. Fractal dimension Correlation dimension Entropy

Conditioning (probability) (6,865 words) [view diff] exact match in snippet view article

+ b2 + c2 = 1). Example. A different measure of calculating the marginal distribution function is provided below f X , Y , Z ( x , y , z ) = 3 4 π {\displaystyle

Distribution of the product of two random variables (7,762 words) [view diff] exact match in snippet view article find links to article

+\gamma }{2}}|z|\right),\;\;-\infty <z<\infty .} The pdf gives the marginal distribution of a sample bivariate normal covariance, a result also shown in

History of network traffic models (3,516 words) [view diff] exact match in snippet view article find links to article

modulo-1 arithmetic. They aim to capture both auto-correlation and marginal distribution of empirical data. TES models consist of two major TES processes:

Discrete Universal Denoiser (4,987 words) [view diff] exact match in snippet view article find links to article

_{X|z}\right)} . This optimal denoiser can be expressed using the marginal distribution of Z {\displaystyle Z} alone, as follows. When the channel matrix

Stable count distribution (7,739 words) [view diff] exact match in snippet view article find links to article

Section 7 of ). Thus the stable count distribution is the first-order marginal distribution of a volatility process. In this context, ν 0 {\displaystyle \nu

E-values (5,389 words) [view diff] exact match in snippet view article find links to article

, then we can set Q {\displaystyle Q} as above to be the Bayes marginal distribution with density q ( Y ) = ∫ q θ ( Y ) w ( θ ) d θ {\displaystyle q(Y)=\int