Unified Theory and Strategies of Survey Sampling
Sample survey is universally recognized as a vital method of data collection to derive reliable statistics on a variety of topics. This volume is mainly concerned with the foundational aspects of inference and the description and comparison of various sampling strategies.
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Admissibility and other optimality properties
Sample Survey and General Statistical Model
11 other sections not shown
approximate Arnab asymptotic Basu Bayes estimator Bayesian Brewer C.R. Rao Chaudhuri class of estimators conditional probabilities considered denote Draw one element drawn equal estimand finite population fixed given Godambe Godambe's h admissible Hanurav hence HLUE Horvitz-Thompson inference itPS Joshi labels Lahiri estimator likelihood likelihood principle linear estimators loss function mean mean square error Meeden method minimax Murthy non-negative obtained optimal order inclusion probabilities parameter permutation permutation model posterior postulated predictor prior probability distribution probability sampling procedure random number random sample ratio estimator rejective sampling sampling design sampling schemes satisfied second order inclusion selection probabilities simple random sampling Singh square error SRSWOR sufficient statistic Sukhatme survey sampling UMVE unbiased estimator unbiased variance estimator unequal probabilities uniform admissibility uniformly units unordered values variable variate-values varying probabilities vector