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150324s1986 xx |||||o 00| ||eng c |
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|a 10.2307/1403146
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|a (DE-627)JST041663829
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|a (JST)1403146
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Royall, Richard M.
|e verfasserin
|4 aut
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|a Model Robust Confidence Intervals Using Maximum Likelihood Estimators
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|c 1986
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|a Text
|b txt
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|a Computermedien
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|a Online-Ressource
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|a Standard large-sample confidence intervals about a maximum likelihood estimator θ̂ are two-thirds robust; i.e. when the parametric model is imperfect θ̂ often remains consistent and asymptotically normal. The confidence intervals are invalidated only because the third necessary condition, consistency of the variance estimator, fails. The 'delta method' provides a simple alternative variance estimator which remains consistent under more general conditions and provides robust large-sample confidence intervals. /// Les intervalles de confiance habituels calculés à partir de la théorie des grands échantillons des estimateurs du maximum de vraisemblance sont robustes à deux tiers-lorsque le modèle paramétrique fait défaut, l'estimateur du maximum de vraisemblance θ̂ demeure souvent consistant et asymptotiquement normal. Les intervalles de confiance sont invalidés seulement à cause de l'échec de la troisième condition nécessaire: la consistance de l'estimateur de la variance. La "méthode delta" fournit un estimateur alternatif simple de la variance qui demeure consistant sous des conditions plus générales et qui donne par conséquent des intervalles de confiance robustes.
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|a Copyright 1986 International Statistical Institute
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|a Asymptotic normality
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|a Information matrix
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|a Large-sample theory
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|a Maximum likelihood estimate
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|a Robustness
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|a Confidence intervals
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|a Mathematics
|x Applied mathematics
|x Analytics
|x Analytical estimating
|x Maximum likelihood estimation
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Measures of variability
|x Statistical variance
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical results
|x Statistical properties
|x Estimate reliability
|x Confidence interval
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
|x Maximum likelihood estimators
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|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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|a Mathematics
|x Pure mathematics
|x Linear algebra
|x Matrix theory
|x Matrices
|x Covariance matrices
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Inferential statistics
|x Statistical estimation
|x Estimation methods
|x Estimators
|x Consistent estimators
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|a Mathematics
|x Pure mathematics
|x Probability theory
|x Random variables
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|a Arts
|x Performing arts
|x Music
|x Music theory
|x Musical pitch
|x Musical intervals
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Thought processes
|x Reasoning
|x Inference
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|a research-article
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|i Enthalten in
|t International Statistical Review / Revue Internationale de Statistique
|d Blackwell Publishing Ltd
|g 54(1986), 2, Seite 221-226
|w (DE-627)327815280
|w (DE-600)2045049-7
|x 17515823
|7 nnns
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|g volume:54
|g year:1986
|g number:2
|g pages:221-226
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|u https://www.jstor.org/stable/1403146
|3 Volltext
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|u https://doi.org/10.2307/1403146
|3 Volltext
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|d 54
|j 1986
|e 2
|h 221-226
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