In statistics, an L-estimator is an estimator which is a linear combination of order statistics of the measurements ( also called an L-statistic). This...

statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity...

In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value...

In statistics, a consistent estimator or asymptotically consistent estimator is an estimator—a rule for computing estimates of a parameter θ0—having the...

The Kaplan–Meier estimator, also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime...

In statistics, M-estimators are a broad class of extremum estimators for which the objective function is a sample average. Both non-linear least squares...

A Newey–West estimator is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model...

of quality of an estimator, of an experimental design, or of a hypothesis testing procedure. Essentially, a more efficient estimator needs fewer input...

In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter...

The James–Stein estimator is a biased estimator of the mean, θ {\displaystyle {\boldsymbol {\theta }}} , of (possibly) correlated Gaussian distributed...

narrower terms according to use, namely: L-estimator, using L-statistics as estimators for parameters L-moment, L-statistic analogs of the conventional moments...

maximally efficient estimator for the center of a uniform distribution, trimmed mid-ranges address robustness, and as an L-estimator, it is simple to understand...

minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than...

midhinge, but unlike the sample mean, it is a statistically resistant L-estimator with a breakdown point of 25%. This beneficial property has been described...

can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when the random...

ordinary least squares (OLS) estimator has the lowest sampling variance within the class of linear unbiased estimators, if the errors in the linear regression...

population L-moments. Sample L-moments can be defined for a sample from the population, and can be used as estimators of the population L-moments. For...

In statistics, a trimmed estimator is an estimator derived from another estimator by excluding some of the extreme values, a process called truncation...

range are not. Trimmed estimators and Winsorised estimators are general methods to make statistics more robust. L-estimators are a general class of simple...

Regular estimators are a class of statistical estimators that satisfy certain regularity conditions which make them amenable to asymptotic analysis. The...

interested in estimating the shape of this function ƒ. Its kernel density estimator is f ^ h ( x ) = 1 n ∑ i = 1 n K h ( x − x i ) = 1 n h ∑ i = 1 n K ( x...

data analysis the term fixed effects estimator (also known as the within estimator) is used to refer to an estimator for the coefficients in the regression...

square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE), which is a common measure of estimator quality, of the...

(MVU) estimator. However, in some cases, no unbiased technique exists which achieves the bound. This may occur either if for any unbiased estimator, there...

statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average...

generally, a point estimator can be contrasted with a set estimator. Examples are given by confidence sets or credible sets. A point estimator can also be contrasted...

concept of being an invariant estimator is a criterion that can be used to compare the properties of different estimators for the same quantity. It is...

Equivalently, it is the 25% trimmed mid-range or 25% midsummary; it is an L-estimator. MH ⁡ ( X ) = Q 1 , 3 ( X ) ¯ = Q 1 ( X ) + Q 3 ( X ) 2 = P 25 ( X )...

summary. In addition, the box-plot allows one to visually estimate various L-estimators, notably the interquartile range, midhinge, range, mid-range, and trimean...

{X}},} an estimator (estimation rule) δ M {\displaystyle \delta ^{M}\,\!} is called minimax if its maximal risk is minimal among all estimators of θ {\displaystyle...