Estimator
Estimator It has been suggested that this article ... with estimation theory. (Discuss) In statistics, an estimator is a function of the known sample ... cannot be used to clearly pick one estimator over another. To estimate a parameter of ... interval estimators. Point estimators For a point estimator $\backslash widehat\{\backslash theta\}$ of parameter is an unbiased estimator of θ iff $B(\backslash widehat\{\backslash \; ...$
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Talk:Estimator
Talk:Estimator θ is an unbiased estimator of θ iff B(θ) = 0 for ... values of theta. B depends on the estimator (function of data) but also on the ... knowing it you design a procedure (the estimator) to compute an estimate from the data ... and this holds for all θ, the estimator is unbiased. Patrick 20:31 Dec ...
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M-estimator
M-estimator In statistics, M-estimators are a type of estimator whose properties are quite well-known. The ... likelihood estimators. When using a maximum likelihood estimator, the aim is to maximize $\backslash prod\_\; ...\; not\; possible,\; we\; speak\; of\; an\; M-$estimator of ρ-type. Otherwise, the M-estimator is said to be of ψ- ...
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James-Stein estimator
James-Stein estimator The James-Stein estimator is a nonlinear estimator which can be shown to dominate, or outperform, the ordinary (least squares) estimator. As such, it is the best-known ... s phenomenon. An earlier version of the estimator was developed by Stein (1956), and ...
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Good–Turing estimator
Good–Turing estimator The Good–Turing estimator (named after I. J. Good and Alan ... Laplace and is called the Laplace-Bayes estimator or the rule of succession. For example ...
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Kaplan-Meier estimator
Kaplan-Meier estimator The Kaplan-Meier estimator provides an estimation of the survivor function ... Real-time example of the Kaplan-Meier estimator in Java Calculating Kaplan-Meier curves by ...
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Talk:Kaplan-Meier estimator
Talk:Kaplan-Meier estimator This entry needs more examples, possibly a ...
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Minimum-variance unbiased estimator
Minimum-variance unbiased estimator In statistics, and more specifically in estimation theory, a minimum-variance unbiased estimator (MVUE or MVU estimator) is an unbiased estimator of parameters, whose variance is minimized for ... all values of the parameters. If an estimator is unbiased, then its mean squared ...
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Talk:Minimum-variance unbiased estimator
Talk:Minimum-variance unbiased estimator Michael Hardy wrote: Deleting nonsense. I already ... the MVUE (if it exists). If the estimator is unbiased then minimizing the variance is ... 00, 10 Mar 2005 (UTC) IF and estimator is unbiased. Read the line above! That ... be saying that the minimum-variance unbiased estimator has the smallest MSE of ANY estimator, since it has the smallest MSE ...
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Estimation theory
... this article or section be merged with estimator. (Discuss) Estimation theory is a branch of ... that answers a question posed by the estimator. For example, it is desired to estimate ... estimation theory is to arrive at an estimator, and preferably an implementable one that could actually be used. The estimator takes the measured data as input and ... It is also preferable to derive an estimator that exhibits optimality. An optimal estimator ...
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