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Longer titles found: Bias of an estimator (view), Minimum-variance unbiased estimator (view), Bayes estimator (view), Kaplan–Meier estimator (view), M-estimator (view), Nelson–Aalen estimator (view), Hodges–Lehmann estimator (view), Consistent estimator (view), Newey–West estimator (view), Civil estimator (view), Building estimator (view), Theil–Sen estimator (view), James–Stein estimator (view), Arellano–Bond estimator (view), Invariant estimator (view), Minimax estimator (view), Delaunay tessellation field estimator (view), Trimmed estimator (view), L-estimator (view), Leonard–Merritt mass estimator (view), Horvitz–Thompson estimator (view), Redescending M-estimator (view), Sieve estimator (view), Fire urgency estimator in geosynchronous orbit (view), Ratio estimator (view), Maximum score estimator (view), Hodges' estimator (view), Extremum estimator (view), Krichevsky–Trofimov estimator (view), First-difference estimator (view), Two-step M-estimator (view), Testimator (view), Adaptive estimator (view), Multi-fractional order estimator (view), Basic pitch count estimator (view), Quaternion estimator algorithm (view)

searching for Estimator 45 found (1749 total)

alternate case: estimator

Continuous uniform distribution (4,230 words) [view diff] exact match in snippet view article find links to article

b]} with unknown b , {\displaystyle b,} the minimum-variance unbiased estimator (UMVUE) for the maximum is: b ^ UMVU = k + 1 k m = m + m k , {\displaystyle

Heavy-tailed distribution (2,705 words) [view diff] exact match in snippet view article find links to article

The ratio estimator (RE-estimator) of the tail-index was introduced by Goldie and Smith. It is constructed similarly to Hill's estimator but uses a non-random

Random effects model (1,216 words) [view diff] exact match in snippet view article find links to article

variables. If the random effects assumption holds, the random effects estimator is more efficient than the fixed effects model. Suppose m {\displaystyle

K-nearest neighbors algorithm (4,333 words) [view diff] exact match in snippet view article find links to article

k-NN is a special case of a variable-bandwidth, kernel density "balloon" estimator with a uniform kernel. The naive version of the algorithm is easy to implement

Generalized Pareto distribution (2,790 words) [view diff] exact match in snippet view article find links to article

approach. A renowned estimator using the POT methodology is the Hill's estimator. Technical formulation of the Hill's estimator is as follows. For 1 ≤

Envelope (waves) (1,844 words) [view diff] no match in snippet view article

In physics and engineering, the envelope of an oscillating signal is a smooth curve outlining its extremes. The envelope thus generalizes the concept of

Variable kernel density estimation (779 words) [view diff] exact match in snippet view article find links to article

estimation. In a balloon estimator, the kernel width is varied depending on the location of the test point. In a pointwise estimator, the kernel width is

Kernel regression (1,261 words) [view diff] exact match in snippet view article find links to article

average, using a kernel as a weighting function. The Nadaraya–Watson estimator is: m ^ h ( x ) = ∑ i = 1 n K h ( x − x i ) y i ∑ i = 1 n K h ( x − x

Root mean square (2,786 words) [view diff] exact match in snippet view article find links to article

estimation theory, the root-mean-square deviation of an estimator measures how far the estimator strays from the data. The RMS value of a set of values

Mark and recapture (3,025 words) [view diff] exact match in snippet view article find links to article

Lincoln–Petersen estimator is asymptotically unbiased as sample size approaches infinity, but is biased at small sample sizes. An alternative less biased estimator of

Base runs (772 words) [view diff] exact match in snippet view article find links to article

reality of the run-scoring process "significantly better than any other run estimator". Base runs has multiple variations, but all take the form A ∗ B B + C

Base runs (772 words) [view diff] exact match in snippet view article find links to article

reality of the run-scoring process "significantly better than any other run estimator". Base runs has multiple variations, but all take the form A ∗ B B + C

Kriging (6,063 words) [view diff] exact match in snippet view article find links to article

related to regression analysis. Both theories derive a best linear unbiased estimator based on assumptions on covariances, make use of Gauss–Markov theorem

Checking whether a coin is fair (2,521 words) [view diff] exact match in snippet view article find links to article

the probabilities that can be counted as "fair" in a practical sense. Estimator of true probability (Frequentist approach). This method assumes that the

Method of conditional probabilities (3,157 words) [view diff] exact match in snippet view article find links to article

the method of conditional probabilities, the technical term pessimistic estimator refers to a quantity used in place of the true conditional probability

Entropy estimation (1,415 words) [view diff] exact match in snippet view article find links to article

such Bayesian estimator was proposed in the neuroscience context known as the NSB (Nemenman–Shafee–Bialek) estimator. The NSB estimator uses a mixture

State observer (5,756 words) [view diff] exact match in snippet view article find links to article

In control theory, a state observer, state estimator, or Luenberger observer is a system that provides an estimate of the internal state of a given real

Orthogonality principle (1,707 words) [view diff] exact match in snippet view article find links to article

optimality of a Bayesian estimator. Loosely stated, the orthogonality principle says that the error vector of the optimal estimator (in a mean square error

Bernstein–von Mises theorem (1,197 words) [view diff] exact match in snippet view article find links to article

a multivariate normal distribution centered at the maximum likelihood estimator θ ^ n {\displaystyle {\widehat {\theta }}_{n}} with covariance matrix

Cross-entropy method (1,085 words) [view diff] exact match in snippet view article find links to article

noisy objective. The method approximates the optimal importance sampling estimator by repeating two phases: Draw a sample from a probability distribution

Dominating decision rule (162 words) [view diff] no match in snippet view article find links to article

In decision theory, a decision rule is said to dominate another if the performance of the former is sometimes better, and never worse, than that of the

Simultaneous perturbation stochastic approximation (1,555 words) [view diff] exact match in snippet view article find links to article

{\displaystyle i^{th}} component of the symmetric finite difference gradient estimator is: FD: ( g n ^ ( u n ) ) i = J ( u n + c n e i ) − J ( u n − c n e i

Wrapped Cauchy distribution (2,035 words) [view diff] exact match in snippet view article find links to article

unbiased estimator of e − 2 γ {\displaystyle e^{-2\gamma }} , and ln ⁡ ( 1 / R e 2 ) / 2 {\displaystyle \ln(1/R_{e}^{2})/2} will be a (biased) estimator of

Linear–quadratic–Gaussian control (2,796 words) [view diff] exact match in snippet view article find links to article

linear–quadratic state estimator (LQE)) together with a linear–quadratic regulator (LQR). The separation principle states that the state estimator and the state

Wrapped normal distribution (1,707 words) [view diff] exact match in snippet view article find links to article

unbiased estimator of the first moment. If we assume that the mean μ lies in the interval [−π, π), then Arg z will be a (biased) estimator of the mean μ

Cauchy distribution (6,933 words) [view diff] exact match in snippet view article find links to article

median value of the sample as an estimator of x 0 {\displaystyle x_{0}} and half the sample interquartile range as an estimator of γ {\displaystyle \gamma }

Location estimation in sensor networks (1,984 words) [view diff] exact match in snippet view article find links to article

likelihood estimator (MLE) θ ^ = 1 N ∑ n = 1 N x n {\displaystyle {\hat {\theta }}={\frac {1}{N}}\sum _{n=1}^{N}x_{n}} is an unbiased estimator whose MSE

Isoline retrieval (1,428 words) [view diff] exact match in snippet view article find links to article

a whole field, it is a general, nonlinear inverse method and a robust estimator. Suppose we have, as in contour advection, inferred knowledge of a single

Simultaneous equations model (3,353 words) [view diff] exact match in snippet view article find links to article

specify. A value of α=1 will yield an estimator that is approximately unbiased. The three-stage least squares estimator was introduced by Zellner & Theil

Nucleotide diversity (653 words) [view diff] exact match in snippet view article find links to article

the sample population, and is denoted by π {\displaystyle \pi } . An estimator for π {\displaystyle \pi } is given by: π ^ = n n − 1 ∑ i j x i x j π

UShip (524 words) [view diff] exact match in snippet view article find links to article

deliver shipments through uShip. uShip has developed a Shipping Price Estimator, which provides estimates for transport services based on a weighted average

Wishart distribution (4,194 words) [view diff] exact match in snippet view article find links to article

Wishart distribution is the sampling distribution of the maximum-likelihood estimator (MLE) of the covariance matrix of a multivariate normal distribution.

WOBA (831 words) [view diff] exact match in snippet view article find links to article

2008. "The great run estimator shootout (part 1) - The Hardball Times". www.fangraphs.com. 9 April 2009. "The great run estimator shootout (part 2) - The

Hannan–Quinn information criterion (491 words) [view diff] exact match in snippet view article find links to article

287). They also note that HQIC, like BIC, but unlike AIC, is not an estimator of Kullback–Leibler divergence. Claeskens and Hjort note that HQC, like

Passing–Bablok regression (759 words) [view diff] exact match in snippet view article find links to article

create an approximately consistent estimator. The estimator is therefore close in spirit to the Theil-Sen estimator. The parameter a {\displaystyle a}

Multitaper (1,510 words) [view diff] exact match in snippet view article find links to article

multitaper spectral estimator utilizes several different data tapers which are orthogonal to each other. The multitaper cross-spectral estimator between channel

Gravity model of trade (3,072 words) [view diff] exact match in snippet view article find links to article

_{3}\ln(D_{ij})]\eta _{ij},} using a Poisson pseudo-maximum likelihood (PPML) estimator based on the Poisson model usually used for count data. As shown by Santos

Dummy variable (statistics) (722 words) [view diff] exact match in snippet view article

only if spring, otherwise equals zero. In the panel data fixed effects estimator dummies are created for each of the units in cross-sectional data (e.g

Yule–Simon distribution (1,312 words) [view diff] exact match in snippet view article find links to article

the standard error of the estimator from the fixed point equation. The variance of the λ {\displaystyle \lambda } estimator is Var ⁡ ( λ ^ ) = 1 N λ ^

Unseen species problem (1,979 words) [view diff] exact match in snippet view article find links to article

samples. The unseen species problem also applies more broadly, as the estimators can be used to estimate any new elements of a set not previously found

Power law (8,193 words) [view diff] exact match in snippet view article find links to article

{\alpha }}-1}{\sqrt {n}}}+O(n^{-1})} . This estimator is equivalent to the popular[citation needed] Hill estimator from quantitative finance and extreme value

Von Mises distribution (2,641 words) [view diff] exact match in snippet view article find links to article

} In other words, z ¯ {\displaystyle {\overline {z}}} is an unbiased estimator of the first moment. If we assume that the mean μ {\displaystyle \mu }

Chebyshev center (1,507 words) [view diff] exact match in snippet view article find links to article

parameter estimation, the Chebyshev center approach tries to find an estimator x ^ {\displaystyle {\hat {x}}} for x {\displaystyle x} given the feasibility

Exponential distribution (6,647 words) [view diff] exact match in snippet view article find links to article

not an unbiased estimator of λ , {\displaystyle \lambda ,} although x ¯ {\displaystyle {\overline {x}}} is an unbiased MLE estimator of 1 / λ {\displaystyle

Buffon's needle problem (4,303 words) [view diff] exact match in snippet view article find links to article

able to determine which of these estimators is a better estimator for π. For the Laplace variant, let p̂ be the estimator for the probability that there