Optimal decisions under uncertainty. Lecture notes in economics and mathematical systems ; 193

Sengupta, Jati K. :

ISBN 10: 3540108696 / ISBN 13: 9783540108696

Published by Berlin ; Heidelberg ; New York : Springer, 1981

About this Item

156 S. ; 25 cm exBibliotheksexemplar mit den üblichen Stempeln/Signaturen, Kanten gering berieben, starke papierbedingte Seitenbräunung /// Standort Wimregal NIKK-4133 ISBN 9783540108696 Sprache: Englisch Gewicht in Gramm: 281.

Seller Inventory # 180953

Bibliographic Details

• Title: Optimal decisions under uncertainty. Lecture notes in economics and mathematical systems ; 193
• Publisher: Berlin ; Heidelberg ; New York : Springer
• Publication Date: 1981
• Language: English
• ISBN 10: 3540108696
• ISBN 13: 9783540108696
• Binding: Broschur
• Condition: Befriedigend
• Weight: 281 grams
• Seller catalogs:
  • Wirtschaft

About this title

Synopsis

The theory of optimal decisions in a stochastic environment has seen many new developments in recent years. The implications of such theory for empirical and policy applications are several. This book attempts to analyze some of the impor­ tant applied aspects of this theory and its recent developments. The stochastic environment is considered here in specific form, e.g., (a) linear programs (LP) with parameters subject to a probabilistic mechanism, (b) decision models with risk aversion, (c) resource allocation in a team, and (d) national economic planning. The book attempts to provide new research insights into several areas, e.g., (a) mixed strategy solutions and econometric tests of hypotheses of LP models, (b) the dual problems of efficient estimation and optimal regulation, (c) input-output planning under imperfect competition, and (d) linear programs viewed as constrained statistical games. Methods of optimal decision rules developed here for quadratic and linear decision problems are applicable in three broad areas: (a) applied economic models in resource allocation, planning and team decision, (b) operations research models in management decisions involving portfolio analysis and stochastic programming, and (c) systems science models in stochastic control and adaptive behavior. Some results reported here have been published in professional journals be-. fore, and I would like to thank the following journals in particular: Inter­ national Journal of Systems Science, Journal of Optimization Theory and Applica­ tions and Journal of Mathematical Analysis and Applications.