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                                       Details for article 9 of 16 found articles
 
 
  Extension of a Two-Stage Conditionally Unbiased Estimator of the Selected Population to the Bivariate Normal Case
 
 
Title: Extension of a Two-Stage Conditionally Unbiased Estimator of the Selected Population to the Bivariate Normal Case
Author: Sill, Michael W.
Sampson, Allan R.
Appeared in: Communications in statistics
Paging: Volume 36 (2007) nr. 4 pages 801-813
Year: 2007-03
Contents: Cohen and Sackrowitz (1989) derive a uniformly minimum variance conditionally unbiased estimator (UMVCUE) for the mean of a selected population for the univariate normal case with variance known and unknown as well as for the gamma case in a two-stage design. We extend this methodology to the bivariate normal case where the covariance matrix is assumed to be known. The population with the largest sample mean of the first dimension is selected for additional observations in a second stage. The goal of the analysis is to find an unbiased estimate of the mean of the second dimension with all of the data.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 9 of 16 found articles
 
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