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|a (DE-627)JST077683285
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|a (JST)25053446
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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1 |
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|a Kubokawa, Tatsuya
|e verfasserin
|4 aut
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| 245 |
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|a Estimation of a Mean of a Normal Distribution with a Bounded Coefficient of Variation
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|c 2005
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|a Text
|b txt
|2 rdacontent
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|a Computermedien
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|2 rdamedia
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|a Online-Ressource
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|a The estimation of a mean of a normal distribution with an unknown variance is addressed under the restriction that the coefficient of variation is within a bounded interval. The paper constructs a class of estimators improving upon the best location-scale equivariant estimator of the mean. It is demonstrated that the class includes three typical estimators: the generalized Bayes estimator based on the uniform prior over the restricted region, the generalized Bayes estimator based on the prior putting mass on the boundary, and a truncated estimator. The non-minimaxity of the best location-scale equivariant estimator is shown in the general location-scale family. When another type of restriction is considered, however, we have a different story that the best location-scale equivariant estimator remains minimax.
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|a Copyright 2005 Indian Statistical Institute
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|a Primary 62C10
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|a Secondary 62C20
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| 650 |
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|a Secondary 62F10
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| 650 |
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|a Bounded mean
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| 650 |
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|a Coefficient of variation
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| 650 |
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|a Decision theory
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| 650 |
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|a Generalized Bayes estimator
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| 650 |
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|a Location-scale family
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| 650 |
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|a Minimaxity
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| 650 |
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|a Restricted parameters
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| 650 |
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Decision making
|x Bayesian theories
|x Bayes estimators
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| 650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
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| 650 |
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4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
|x Unbiased estimators
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| 650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Game theory
|x Minimax
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| 650 |
|
4 |
|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Decision making
|x Bayesian theories
|x Bayes theorem
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| 650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Statistical distributions
|x Distribution functions
|x Probability distributions
|x Gaussian distributions
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| 650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
|x Estimators of variance
|x Estimators for the mean
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| 650 |
|
4 |
|a Mathematics
|x Pure mathematics
|x Probability theory
|x Random variables
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| 650 |
|
4 |
|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
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| 650 |
|
4 |
|a Mathematics
|x Mathematical expressions
|x Parametric Estimation
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| 655 |
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4 |
|a research-article
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| 773 |
0 |
8 |
|i Enthalten in
|t Sankhyā: The Indian Journal of Statistics (2003-2007)
|d Indian Statistical Institute, 1933
|g 67(2005), 3, Seite 499-525
|w (DE-627)37948224X
|w (DE-600)2135890-4
|x 09727671
|7 nnns
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| 773 |
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|g volume:67
|g year:2005
|g number:3
|g pages:499-525
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|u https://www.jstor.org/stable/25053446
|3 Volltext
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|d 67
|j 2005
|e 3
|h 499-525
|