Bootstrap confidence bands for shrinkage estimators
作者： Camilla Kazimi , David Brownstone
DOI: 10.1016/S0304-4076(98)00037-2
关键词: Confidence and prediction bands 、 Bootstrapping (electronics) 、 Confidence interval 、 Edgeworth series 、 Econometrics 、 Probability distribution 、 Statistics 、 Mathematics 、 Monte Carlo method 、 Percentile 、 Estimator
摘要: Empirical application of shrinkage estimators has been limited by the inability to estimate confidence intervals. We investigate band based on Edgeworth expansions and bootstrapping. Our Monte Carlo results suggest that both Efron's bias correction method with acceleration simple percentile bootstrap methods generate reasonable bands. Approximations performed poorly. then use a single bands for predictions GNP growth rates from leading-indicators model. study shows perform well enough support empirical applications estimators.
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