Design and Inference in Finite Population Sampling

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...

Nonparametric Inference Under Biased Sampling from a Finite Population

Bayesian penalized spline model-based inference for finite population proportion in unequal probability sampling.

We propose a Bayesian Penalized Spline Predictive (BPSP) estimator for a finite population proportion in an unequal probability sampling setting. This new method allows the probabilities of inclusion to be directly incorporated into the estimation of a population proportion, using a probit regression of the binary outcome on the penalized spline of the inclusion probabilities. The posterior pre...

The bootstrap and finite population sampling.

Synthetic populations are used to study methods for adapting Efron’s bootstrap estimation technique to finite population sampling. Of particular interest is the extention of these methods to two-stage cluster sampling. Using simulations based on five artificial populations, two variations of bootstrap estimators and two Taylor series variance estimators for a ratio estimator are compared by mea...

Using Prior Information about Population Quantiles in Finite Population Sampling

Many classical methods in finite population sampling have been developed to incorporate some fairly standard types of prior information about the population. When the prior information does not fall in the standard categories it can be difficult to find procedures which reflect the information and have good frequentist properties. Recently methods based on the empirical likelihood were consider...