Estimation under sampling from a finite population

Nonparametric Inference Under Biased Sampling from a Finite Population

Design Based Estimation of Finite Population Mean in Ranked Set Sampling

Abstract. This Article introduce method of ranked set sampling with replacement (RSSWR) in finite population and express how to computing samples of inclusion probability for this method. The Horvitz-Thompson and Hansen-Hurwtz estimators using auxiliary variables introduce for this design and use 2011-12 Urban Households Income and Income and Expenditure survey data, gathered for Tehran by stat...

Non-response in Sampling from a Dichotomous Finite Population Non-response in Sampling from a Dichotomous Finite Population (^223^66)

Nonparametric Regression Estimation of Finite Population Totals under Two-Stage Sampling

We consider nonparametric regression estimation for finite population totals for two-stage sampling, in which complete auxiliary information is available for first-stage sampling units. The estimators, based on local polynomial regression, are linear combinations of cluster total estimators, with weights that are calibrated to known control totals. The estimators are asymptotically design-unbia...

Finite population estimation under generalized linear model assistance

Finite population estimation is the overall goal of sample surveys. When information regarding auxiliary variables are available, one may take advantage of general regression estimators (GREG) to improve sample estimate precision. GREG estimators may be derived when the relationship between interest and auxiliary variables is represented by a normal linear model. However, in some scenarios, suc...