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| Author | : Shanti S. Gupta |
| Publisher | : SIAM |
| Total Pages | : 592 |
| Release | : 2002-01-01 |
| Genre | : Mathematics |
| ISBN | : 0898715326 |
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.
| Author | : Shanti S. Gupta |
| Publisher | : |
| Total Pages | : 93 |
| Release | : 1971 |
| Genre | : |
| ISBN | : |
The report is a survey of developments and significant results in the area of multiple decision procedures under the subset selection formulation. Section 2 deals with procedures for location and scale parameters. A general theory of the subset selection problem and a decision-theoretic formulation are discussed in Section 3. Sections 4 through 7 deal with parametric and non- parametric procedures for discrete populations, multinomial cells and multivariate normal populations using single-stage sampling, inverse sampling and sequential sampling. Section 8 describes procedures applicable to restricted families of distributions such as the increasing failure rate (IFR) and increasing failure rate on the average (IFRA) distributions. Bayes and empirical Bayes procedures are discussed in Section 9. The last section summarizes briefly several modifications of the basic problem and goal.
| Author | : Deng-Yuan Huang |
| Publisher | : |
| Total Pages | : 78 |
| Release | : 1974 |
| Genre | : |
| ISBN | : |
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).
| Author | : Shanti S. Gupta |
| Publisher | : |
| Total Pages | : 19 |
| Release | : 1977 |
| Genre | : |
| ISBN | : |
This paper studies a multiple decision procedure for k(k> or = 2) populations which are themselves unknown but which one assumed to belong to a restricted family. We propose to study a selection procedure for distributions associated with these populations which are convex-ordered with respect to a specified distribution G assuming there exists a best one.
| Author | : Jason C. Hsu |
| Publisher | : |
| Total Pages | : 74 |
| Release | : 1977 |
| Genre | : |
| ISBN | : |
Ranking and selection procedures, subset selection procedures in particular, are procedures that provide in a realistic manner attractive ways of handling problems that are commonly treated by the 2-action procedure of a global F-test, and the many-action procedure of a typical multiple range test. Consider the usual one-way layout situation in analysis of variance. In this situation, formulating the problem as a selection problem is appropriate. Subset selection procedures are often thought of as screening procedures. If the data indicates several treatments are better than the remaining treatments but no treatment is clearly the best, then perhaps the experimenter ought to retain all of the better treatments for future considerations.
| Author | : Shanti S. Gupta |
| Publisher | : |
| Total Pages | : 127 |
| Release | : 1971 |
| Genre | : |
| ISBN | : |
The report is presented in three parts. Part A consists of eight sections and deals with multiple decision (selection and ranking) procedures. Part B contains some distribution theory which arises in these selection and ranking problems and some results relating to the moments of certain statistics. An overall description of the several tables that have been constructed is also given in this part. Part C includes on a variety of topics among which are (i) the distribution of linear functions of ordered correlated normal random variables, (ii) order statistics from the logistic distribution, (iii) inequalities relating to binomial and gamma distributions, (iv) the moments of traces of two matrices that arise in three different situations for complex multivariate normal populations and (v) life testing sampling plans for distributions having an increasing or a decreasing failure rate. (Author).
| Author | : Andrew Scott George |
| Publisher | : |
| Total Pages | : 92 |
| Release | : 1975 |
| Genre | : Correlation (Statistics) |
| ISBN | : |
| Author | : S. Panchapakesan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 478 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461223083 |
Shanti S. Gupta has made pioneering contributions to ranking and selection theory; in particular, to subset selection theory. His list of publications and the numerous citations his publications have received over the last forty years will amply testify to this fact. Besides ranking and selection, his interests include order statistics and reliability theory. The first editor's association with Shanti Gupta goes back to 1965 when he came to Purdue to do his Ph.D. He has the good fortune of being a student, a colleague and a long-standing collaborator of Shanti Gupta. The second editor's association with Shanti Gupta began in 1978 when he started his research in the area of order statistics. During the past twenty years, he has collaborated with Shanti Gupta on several publications. We both feel that our lives have been enriched by our association with him. He has indeed been a friend, philosopher and guide to us.
| Author | : Dieter Rasch |
| Publisher | : John Wiley & Sons |
| Total Pages | : 650 |
| Release | : 2019-08-14 |
| Genre | : Mathematics |
| ISBN | : 1119551544 |
Instructs readers on how to use methods of statistics and experimental design with R software Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds from a strong theoretical background, but it is practically oriented to develop one's ability to tackle new and non-standard problems confidently. Taking a practical approach to applied statistics, this user-friendly guide teaches readers how to use methods of statistics and experimental design without going deep into the theory. Applied Statistics: Theory and Problem Solutions with R includes chapters that cover R package sampling procedures, analysis of variance, point estimation, and more. It follows on the heels of Rasch and Schott's Mathematical Statistics via that book's theoretical background—taking the lessons learned from there to another level with this book’s addition of instructions on how to employ the methods using R. But there are two important chapters not mentioned in the theoretical back ground as Generalised Linear Models and Spatial Statistics. Offers a practical over theoretical approach to the subject of applied statistics Provides a pre-experimental as well as post-experimental approach to applied statistics Features classroom tested material Applicable to a wide range of people working in experimental design and all empirical sciences Includes 300 different procedures with R and examples with R-programs for the analysis and for determining minimal experimental sizes Applied Statistics: Theory and Problem Solutions with R will appeal to experimenters, statisticians, mathematicians, and all scientists using statistical procedures in the natural sciences, medicine, and psychology amongst others.
