## Estimator

In statistics, an **estimator** is a rule for calculating an estimate of a given quantity based on observed data: thus the rule and its result (the estimate) are distinguished.

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### Some articles on estimator:

Stein's Unbiased Risk Estimate

... This is important since the true mean-squared error of an

... This is important since the true mean-squared error of an

**estimator**is a function of the unknown parameter to be estimated, and thus cannot be determined exactly ...Leonard–Merritt Mass

... The Leonard–Merritt mass

**Estimator**... The Leonard–Merritt mass

**estimator**is a formula for estimating the mass of a spherical stellar system using the apparent (angular) positions and proper motions of its component stars ... Like the virial theorem, the Leonard–Merritt**estimator**yields correct results regardless of the degree of velocity anisotropy ... The**estimator**has the general form Like all**estimators**based on moments of the Jeans equations, the Leonard–Merritt**estimator**requires an assumption about the relative distribution ...Redescending M-

... Redescending M-

**estimator**- Advantages... Redescending M-

**estimators**have high breakdown points (close to 0.5), and their Ψ function can be chosen to redescend smoothly to 0 ... are not ignored completely, and greatly improves the efficiency of the redescending M-**estimator**... The redescending M-**estimators**are slightly more efficient than the Huber**estimator**for several symmetric, wider tailed distributions, but about 20% more efficient than the Huber**estimator**for the Cauchy ...L-

... In robust statistics, an L-

**estimator**... In robust statistics, an L-

**estimator**is an**estimator**which equals a linear combination of order statistics of the measurements ... The median is therefore a simple example of an L-**estimator**... Not all L-**estimators**are robust the minimum, maximum, mean, and mid-range are all L-**estimators**, but have a breakdown point of 0 ...**Estimator**- Behavioural Properties

... Consistency A consistent sequence of

**estimators**is a sequence of

**estimators**that converge in probability to the quantity being estimated as the index (usually the sample size) grows without ... In other words, increasing the sample size increases the probability of the

**estimator**being close to the population parameter ... Mathematically, a sequence of

**estimators**{tn n ≥ 0} is a consistent

**estimator**for parameter θ if and only if, for all ϵ > 0, no matter how small, we have The consistency defined above may be ...

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