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M-estimator

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 and maximum likelihood estimation are special cases of M-estimators. The definition of M-estimators was motivated by robust statistics, which contributed new types of M-estimators.[citation needed]…

History, Historical motivation & Computation

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Historical motivation

Definition

Types

Computation

Properties

Examples

Sufficient conditions for statistical consistency

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Map overview Semantic statistics

M-estimator

Nodes45
Edges44
Triples144
Avg. degree1.96
Density0.044444
Components1

How this topic connects Entity context

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M-estimator

Top relations

related to Further reading · 94
M-estimator → Academic Press, Alexander, Alpha Science International, An Introduction, Andersen, Annals, Applications, Applying, Approximation, BP, CA, Cambridge, Cambridge Series, Cambridge University Press, Christopher, Cite, CiteSeerX, Clarendon Press, David, Ed
related to Historical motivation · 11
M-estimator → Although, By, Daniel Bernoulli, De Menezes, Galileo Galilei, Later, M-estimators, Roger Joseph Boscovich, Simon Newcomb, Smith, The
related to Concentrating parameters · 7
M-estimator → Consider, Examples, In, M-estimation, M-estimators, SUR, The
related to Distribution · 5
M-estimator → As, However, It, M-estimators, Wald-type
related to Median · 5
M-estimator → For, While, X1, Xn, Xs
related to ρ-type · 5
M-estimator → An M-estimator, For, It, Sigma, Theta
related to Influence function · 4
M-estimator → IF, Its, Let, The
related to ψ-type · 4
M-estimator → An M-estimator, If, It, Theta
related to Sufficient conditions for statistical consistency · 3
M-estimator → M-estimators, Specifically, Theta
related to External links · 2
M-estimator → M-estimators, Zhengyou Zhang

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Important terminology

function m-estimators displaystyle theta robust maximum isbn statistics likelihood statistical estimator estimating parameters rho estimators ψ-type functions estimation derivative computation

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
M-estimatorhas applicationM-estimators0.60section
M-estimatorrelated to Concentrating parametersIn0.60section
M-estimatorrelated to Concentrating parametersM-estimators0.60section
M-estimatorrelated to Concentrating parametersThe0.60section
M-estimatorrelated to Concentrating parametersExamples0.60section
M-estimatorrelated to Concentrating parametersSUR0.60section
M-estimatorrelated to Concentrating parametersConsider0.60section
M-estimatorrelated to Concentrating parametersM-estimation0.60section
M-estimatorrelated to DistributionIt0.60section
M-estimatorrelated to DistributionM-estimators0.60section
M-estimatorrelated to DistributionAs0.60section
M-estimatorrelated to DistributionWald-type0.60section

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