Author: Shanti S. GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 10
Book Description
This paper concerns the construction of optimal subset selection procedures. Some classical selection procedures are considered as special cases.
A Note on Optimal Subset Selection Procedures
Author: Shanti S. GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 10
Book Description
This paper concerns the construction of optimal subset selection procedures. Some classical selection procedures are considered as special cases.
On Some Methods for Constructing Optimal Subset Selection Procedures
Author: Shanti Swarup GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 10
Book Description
In this paper, we are concerned with the construction of 'optimal' subset selection procedures. Some classical selection procedures are considered as special cases. (Author).
On Optimal Subset Selection Procedures
Author: Jan Fredrik BjornstadPublisher:
ISBN:
Category :
Languages : en
Pages : 244
Book Description
Locally Optimal Subset Selection Procedures Based on Ranks
Author: Shanti S. GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 16
Book Description
This paper deals with subset selection rules based on ranks in the pooled sample. The procedures satisfy the P-condition and also locally maximize the probability of a correct selection. An application to a problem in regression analysis is provided. (Author).
Multiple Decision Procedures
Author: Shanti S. GuptaPublisher: 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.
Machine Learning Under a Modern Optimization Lens
Author: Dimitris BertsimasPublisher:
ISBN: 9781733788502
Category : Machine learning
Languages : en
Pages : 589
Book Description
On Some Optimal Subset Selection Procedures for Model I and Model II in Treatments Versus Control Problems
Author: Deng-Yuan HuangPublisher:
ISBN:
Category :
Languages : en
Pages : 14
Book Description
Some optimal subset selection procedures for model 1 problem are derived to select a subset which contains all 'positive' populations while controlling 'false' positives. For model 2 problem, the optimal subset selections procedure are to select all positive populations while rejecting all negative ones. The Gamma-minimax selection procedures are considered for the general family of distributions. (Author).
Optimality of subset selection procedures for ranking means of three normal populations
Author: Shanti Swarup GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 24
Book Description
This paper deals with the classical Gupta (1956,65)-approach (Minimize the expected subset size under the P*-condition) in the case of three normal populations with a common known variance and equal sample sizes n. By the method of Lagrangian (undetermined) multipliers a function (involving psi and phi-terms only) is derived which is a convenient tool to find optimal procedures within Seal's (1955,57) class. Numerical work together with asymptotical results lead to the conclusion that for every fixed P* and mean vector mu, Gupta's (1956) means procedure is optimal within Seal's class for sufficiently large sample size n. (Author).
On Subset Selection Procedures for the T Best Populations
Author: Shanti S. GuptaPublisher:
ISBN:
Category :
Languages : en
Pages : 10
Book Description
In the paper, the authors are interested in deriving a procedure which selects a random size subset containing all the t best populations, with a probability not less than P*, a specified constant.
Some Contributions to Fixed Sample and Sequential Multiple Decision (Selection and Ranking) Theory
Author: Deng-Yuan HuangPublisher:
ISBN:
Category :
Languages : en
Pages : 78
Book Description
The report makes some contributions to the subset selection procedures - both for the fixed sample and the sequential case. Chapter 1 deals with some subset selection procedures for binomial populations in terms of the entropy functions, which is different from the usual selection problem in terms of the success probabilities. In Chapter 2, some fixed sample optimal subset selection procedures are discussed for model I and II problems in the analysis of variance in treatments versus control, and a method for constructing some subset selection procedures is derived. Chapter 3 discusses a method for constructing some sequential subset selection procedures and some optimal sequential subset selection procedure in treatments versus control. An upper bound on the expected sample size for Bechhofer-Kiefer-Sobel sequential selection procedure with indifference zone approach is also derived. (Author).