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Mathematical Programming in Sample Surveys

Irfan Ali

ISBN 10: 3659135526 / ISBN 13: 9783659135521
Editorial: LAP LAMBERT Academic Publishing
Nuevos Condición: New Encuadernación de tapa blanda
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Descripción

Paperback. 232 pages. Dimensions: 8.7in. x 5.9in. x 0.5in.This book is based on the applications of mathematical programming techniques in multivariate sample surveys. The various multi-objective techniques namely chebyshev approximation, goal programming, lexicographic goal programming, fuzzy programming, D1-distances, E- constraint, value function and Distance-based etc. , have been used to solve the multi-objective multivariate stratified sample survey problems. The non response case in multi-objective multivariate stratified sample surveys problem is also considered and the compromise allocations of samples are obtained. Allocation problems arising in sample surveys with stochastic parameters have also been discussed. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm. The new cut method, confidence interval and geometric programming are used to obtain the allocations in sample surveys. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. N° de ref. de la librería 9783659135521

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Título: Mathematical Programming in Sample Surveys

Editorial: LAP LAMBERT Academic Publishing

Encuadernación: Paperback

Condición del libro:New

Tipo de libro: Paperback

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Sinopsis:

This book is based on the applications of mathematical programming techniques in multivariate sample surveys. The various multi-objective techniques namely chebyshev approximation, goal programming, lexicographic goal programming,fuzzy programming, D1-distances, E- constraint, value function and Distance-based etc., have been used to solve the multi-objective multivariate stratified sample survey problems. The non response case in multi-objective multivariate stratified sample surveys problem is also considered and the compromise allocations of samples are obtained. Allocation problems arising in sample surveys with stochastic parameters have also been discussed. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm. The new cut method, confidence interval and geometric programming are used to obtain the allocations in sample surveys.

About the Author:

Irfan Ali received M.Sc. M. Phil. and Ph.D.in Statistics from Aligarh Muslim University,Aligarh, India. He has more than 4 years of experience in research and his current area of research includes Mathematical Programming, Transportation, Sample Surveys and Reliability. He has published more than 25 research papers in reputed journals.

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