This is an advanced course in Sampling Techniques that aims at describing some advanced level topics for students who wish to pursue research in Sampling Techniques. This course prepares students for undertaking research in this area.
Techniques of un-ordering and combined un-ordering. The un-ordering of the most general T class of linear estimators. The combined un-ordering of the classical SRSWR estimator.
Some important results in T1, T2, T7 classes of linear estimators. Unified theory of Godambe: His general class as a special class T7 - Class and some other important results. Concept of Non-linear estimation.
Theory of univariate successive sampling on h occasions & its applications. Stratification problems: Construction of strata, declaration of Strata boundaries & its approximate solutions in different allocations. Sufficiency in sampling theory and its applications to improve classical SRSWR estimator.
Estimation in deep-stratification, Sources of non- response, Post-stratification, Mean estimation in post-stratification. Sukhatme, Tukey and Robson’s main results on symmetric functions and Polyksa.
Issues in small area estimation- synthetic and generalized regression estimators. Variance estimation, method of random groups, balanced half samples (IPNSS), Jack-Knife method.
Books Recommended/References: