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In this article we have proposed an efficient generalised class of estimator using two auxiliary variables for estimating unknown population variance 2 yS of study variable y .We have also extended our problem to the case of two phase sampling. In support of theoretical results we have included an empirical study.
A comprehensive expose of basic and advanced sampling techniques along with their applications in the diverse fields of science and technology.
In this paper exponential ratio and exponential product type estimators using two auxiliary variables are proposed for estimating unknown population variance 2 yS . Problem is extended to the case of two-phase sampling. Theoretical results are supported by an empirical study.
The development of estimators of population parameters based on two-phase sampling schemes has seen a dramatic increase in the past decade. Various authors have developed estimators of population using either one or two auxiliary variables. The present volume is a comprehensive collection of estimators available in single and two phase sampling. The book covers estimators which utilize information on single, two and multiple auxiliary variables of both quantitative and qualitative nature. The estimators discussed in the text are based upon different mechanisms of the availability of auxiliary information, termed here as Full, Partial and No Information. Multivariate estimators in survey sampling are also discussed in the book. Two Phase Sampling will prove an invaluable point of reference for researchers working in the field of survey sampling in general and in the field of two-phase sampling in particular.
Ranked Set Sampling is one of the new areas of study in this region of the world and is a growing subject of research. Recently, researchers have paid attention to the development of the types of sampling; though it was not welcome in the beginning, it has numerous advantages over the classical sampling techniques. Ranked Set Sampling is doubly random and can be used in any survey designs. The Pakistan Journal of Statistics had attracted statisticians and samplers around the world to write up aspects of Ranked Set Sampling. All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics. The subject is still a hot topic for MPhil and PhD students for their dissertations.
"Ratio Method of Estimation - This is an ideal textbook for researchers interested in sampling methods, survey methodologists in government organizations, academicians, and graduate students in statistics, mathematics and biostatistics. This textbook makes"
Basic theory: simple random sampling. Sampling with varying probabilities. Stratified sampling. Ratio method of estimation. Regression method estimation. Choice of sampling unit. Sub-sampling. Systematic sampling. Non-sampling errors.
This book is a multi-purpose document. It can be used as a text by teachers, as a reference manual by researchers, and as a practical guide by statisticians. It covers 1165 references from different research journals through almost 1900 citations across 1194 pages, a large number of complete proofs of theorems, important results such as corollaries, and 324 unsolved exercises from several research papers. It includes 159 solved, data-based, real life numerical examples in disciplines such as Agriculture, Demography, Social Science, Applied Economics, Engineering, Medicine, and Survey Sampling. These solved examples are very useful for an understanding of the applications of advanced sampling theory in our daily life and in diverse fields of science. An additional 173 unsolved practical problems are given at the end of the chapters. University and college professors may find these useful when assigning exercises to students. Each exercise gives exposure to several complete research papers for researchers/students.
Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.