首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Asymptotic properties of a generalized regression-type predictor of a finite population variance in probability sampling
Authors:D N Shah  P A Patel
Abstract:A system of predictors for estimating a finite population variance is defined and shown to be asymptotically design-unbiased (ADU) and asymptotically design-consistent (ADC) under probability sampling. An asymptotic mean squared error (MSE) of a generalized regression-type predictor, generated from the system, is obtained. The suggested predictor attains the minimum expected variance of any design-unbiased estimator when the superpopulation model is correct. The generalized regression-type predictor and the predictor suggested by Mukhopadhyay (1990) are compared.
Keywords:Unequal probability sampling  asymptotic design unbiasedness and consistency  regression model  generalized regression-type predictor  mean squared error  minimum expected variance    AMS 1991 subject classifications: 62D05  62J05  
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号