Statistical decision theory provides a framework on which many statistical procedures may be built and justified. It is not exclusively a subdicipline of statistics, and can also provide models for academic disciplines ranging from history and economics to psychology, political science and research. Statisticians need to understand the mathematics and techniques of decision analysis so that their inferential methods can interface with the other parts of the analysis. This new addition to 'Kendall's Library of Statistics' presents a broad overview of decision theory and its applications as well as a focus on statistical decision theory.
"Sinopsis" puede pertenecer a otra edición de este libro.
Decision-theoretic ideas can structure the process of inference together with the decision-making that inference supports. Statistical decision theory is the sub-discipline of statistics which explores and develops this structure. Typically, discusion of decision theory within one discipline does not recognise that other disciplines may have considered the same or similar problems. This text, Volume 9 in the prestigious Kendall's Library of Statistics, provides an overview of the main ideas and concepts of statistical decision theory and sets it within the broader concept of decision theory, decision analysis and decision support as they are practised in many disciplines beyond statistics - including artificial intelligence, economics, operational research, philosophy and psychology.
Simon French, University of Manchester, UK.
David Rios Insua, Universidad Rey Juan Carlos, Madrid, Spain.
"Sobre este título" puede pertenecer a otra edición de este libro.
Descripción Hodder Education Publishers, 2000. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería M0340614609