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Ranking and Selection Problems of Normal Population Using the Absolute Values of Their Means

Author: Mohammad Haseeb Rizvi
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 124

Book Description

Multiple Decision Procedures

Author: Shanti S. Gupta
Publisher: SIAM
ISBN: 0898715326
Category : Mathematics
Languages : en
Pages : 592

Book Description
An encyclopaedic coverage of the literature in the area of ranking and selection procedures. It also deals with the estimation of unknown ordered parameters. This book can serve as a text for a graduate topics course in ranking and selection. It is also a valuable reference for researchers and practitioners.

Advances on Theoretical and Methodological Aspects of Probability and Statistics

Author: N. Balakrishnan
Publisher: CRC Press
ISBN: 9780203493205
Category : Mathematics
Languages : en
Pages : 562

Book Description
At the International Indian Statistical Association Conference, held at McMaster University in Ontario, Canada, participants focused on advancements in theory and methodology of probability and statistics. This is one of two volumes containing invited papers from the meeting. The 32 chapters deal with different topics of interest, including stochastic processes and inference, distributions and characterizations, inference, Bayesian inference, selection methods, regression methods, and methods in health research. The text is ideal for applied mathematicians, statisticians, and researchers in the field.

Sequential Identification and Ranking Procedures

Author: Robert Eric Bechhofer
Publisher:
ISBN:
Category : Sequential analysis
Languages : en
Pages : 448

Book Description

A Multiple-decision Approach to the Selection of the Best Set of Predictor Variates

Author: John Schmidt Ramberg
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 230

Book Description
Some 'indifference zone' multiple-decision selection procedure formulations of prediction problems involving multivariate normal populations are considered. These problems are of two types. Part I considers problems involving k bivariate normal populations, where the goal is to select the 'best' population. In this part the 'goodness' of the prediction is measured in terms of three different parameters -- the population conditional variance, the population correlation coefficient, and the absolute value of the population correlation coefficient. Part II considers the problem of selecting the best set of a preassigned number t variates from a set of k predictor variates for predicting a designated variate, the predictand. The 'best' set of predictor variates is defined to be the set of t variates for which the predictand has the smallest population conditional variance (or equivalently the largest population multiple correlation coefficient). Sample size requirements are obtained using asymptotic distribution theory of the transformed statistics.

Ranking and Selection Problems of Normal Population Using the Absolute Values of Their Means

Multiple Decision Procedures

Advances on Theoretical and Methodological Aspects of Probability and Statistics

Sequential Identification and Ranking Procedures

A Multiple-decision Approach to the Selection of the Best Set of Predictor Variates

The Annals of Mathematical Statistics

Technical Report

Some Optimal Properties of Ranking Procedures with Applications in Multivariate Analysis

The Complete Categorized Guide to Statistical Selection and Ranking Procedures

Journal of the American Statistical Association