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Bayesian Confidence Intervals in Penalized Likelihood Regression
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 Title & Authors
Bayesian Confidence Intervals in Penalized Likelihood Regression
Kim Young-Ju;
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 Abstract
Penalized likelihood regression for exponential families have been considered by Kim (2005) through smoothing parameter selection and asymptotically efficient low dimensional approximations. We derive approximate Bayesian confidence intervals based on Bayes model associated with lower dimensional approximations to provide interval estimates in penalized likelihood regression and conduct empirical studies to access their properties.
 Keywords
Bayesian Confidence Interval;Penalized Likelihood;Smoothing Parameter;
 Language
Korean
 Cited by
1.
Penalized Likelihood Regression with Negative Binomial Data with Unknown Shape Parameter,;

Communications for Statistical Applications and Methods, 2007. vol.14. 1, pp.23-32 crossref(new window)
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