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150325s2004 xx |||||o 00| ||eng c |
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|a (DE-627)JST077778243
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|a (JST)4616838
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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 Fushiki, Tadayoshi
|e verfasserin
|4 aut
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|a On Parametric Bootstrapping and Bayesian Prediction
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|c 2004
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|a Text
|b txt
|2 rdacontent
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|a Computermedien
|b c
|2 rdamedia
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|a Online-Ressource
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|a We investigate bootstrapping and Bayesian methods for prediction. The observations and the variable being predicted are distributed according to different distributions. Many important problems can be formulated in this setting. This type of prediction problem appears when we deal with a Poisson process. Regression problems can also be formulated in this setting. First, we show that bootstrap predictive distributions are equivalent to Bayesian predictive distributions in the second-order expansion when some conditions are satisfied. Next, the performance of predictive distributions is compared with that of a plug-in distribution with an estimator. The accuracy of prediction is evaluated by using the Kullback-Leibler divergence. Finally, we give some examples.
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|a Copyright 2004 Board of the Foundation of the Scandinavian Journal of Statistics
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|a asymptotic theory
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|a Bayesian prediction
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|a bootstrap predictive distribution
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|a information geometry
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|a Kullback-Leibler divergence
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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
|x Fisher information
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|a Mathematics
|x Pure mathematics
|x Algebra
|x Coefficients
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Statistical models
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|a Mathematics
|x Pure mathematics
|x Algebra
|x Polynomials
|x Binomials
|x Binomial distributions
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|a Applied sciences
|x Research methods
|x Modeling
|x Predictive modeling
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|a Applied sciences
|x Research methods
|x Modeling
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|a Philosophy
|x Logic
|x Logical topics
|x Formal logic
|x Mathematical logic
|x Denotational semantics
|x Mathematical notation
|x Sigma notation
|x Indices of summation
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Decision making
|x Bayesian theories
|x Bayes theorem
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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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|a research-article
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1 |
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|a Komaki, Fumiyasu
|e verfasserin
|4 aut
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1 |
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|a Aihara, Kazuyuki
|e verfasserin
|4 aut
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0 |
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|i Enthalten in
|t Scandinavian Journal of Statistics
|d Blackwell Publishers, 1974
|g 31(2004), 3, Seite 403-416
|w (DE-627)266018297
|w (DE-600)1466951-1
|x 14679469
|7 nnns
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1 |
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|g volume:31
|g year:2004
|g number:3
|g pages:403-416
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|u https://www.jstor.org/stable/4616838
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|d 31
|j 2004
|e 3
|h 403-416
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