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Shrinkage estimation in pooling data for arbitrary populations
Author(s) -
Ahmed S. E.,
Khan S. M.
Publication year - 1991
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.3770020405
Subject(s) - shrinkage , pooling , estimator , mathematics , statistics , shrinkage estimator , robustness (evolution) , maximum likelihood , econometrics , computer science , efficient estimator , minimum variance unbiased estimator , artificial intelligence , biochemistry , chemistry , gene
The classical problem of pooling data of two independent random samples drawn possibly from two identical arbitrary populations is considered. Decision to pool the two samples or not is based on the outcome of the preliminary test and then a shrinkage technique is used. In an asymptotic setup, the distributional risks of the proposed estimators are derived and compared. This study reveals the robustness property of the proposed shrinkage preliminary test maximum likelihood estimator (SPTMLE) when the assumed restraints may not hold. It is shown that the proposed estimator provides a wider range than the usual preliminary test maximum likelihood estimator (PTMLE) in which it dominates the classical estimator. More importantly, the SPTMLE provides more meaningful size for the preliminary test.