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M-estimates of regression when the scale is unknown and the error distribution is possibly asymmetric: A minimax result
Bing Li
, Ruben H. Zamar
Statistics
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peer-review
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Dive into the research topics of 'M-estimates of regression when the scale is unknown and the error distribution is possibly asymmetric: A minimax result'. Together they form a unique fingerprint.
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Mathematics
Minimax
100%
Asymmetric
100%
Error Distribution
100%
Variance
33%
Gaussian Distribution
33%
Scale Parameter
33%
Regression Model
33%
Regression Coefficient
33%
Optimal Choice
33%
Variance Estimate
33%
Robust Test
33%
Nuisance Parameter
33%
Keyphrases
Minimax
100%
Error Distribution
100%
M-estimate
100%
Scale Parameter
33%
Robust Estimation
33%
Regression Model
33%
Large Classes
33%
Asymptotic Covariance Matrix
33%
Regression Coefficient
33%
Variance Estimate
33%
Nuisance Parameter
33%