1 edition of Probability models and statistical analyses for ranking data found in the catalog.
Probability models and statistical analyses for ranking data
Includes bibliographical references.
|Statement||Michael A. Fligner, Joseph S. Verducci (eds.).|
|Series||Lecture notes in statistics ;, 80, Lecture notes in statistics (Springer-Verlag) ;, v. 80.|
|Contributions||Fligner, Michael A., Verducci, Joseph S.|
|LC Classifications||QA278.75 .P76 1993|
|The Physical Object|
|Pagination||xxiii, 306 p. :|
|Number of Pages||306|
|LC Control Number||92030305|
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Forward to the Book: Probability Models and Statistical Analyses For Ranking Data, Fligner, M., Verducci,J. ed., xvii-xxiii, Springer Lecture Notes in Statistics, 80 Springer, New York Comparison Techniques for Random Walk on Finite Groups. Books shelved as statistics-and-probability: Time Series Analysis: Forecasting and Control by George E.P. Box, Real-Life Math for Probability, Grade
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In June ofa conference was held on Probablity Models and Statisti cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians.
The conference took place at. In June ofa conference was held on Probablity Models and Statisti cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians. This book of edited contributions provides a wide-ranging survey of the use of probability models for ranking data and it introduces new methods for the statistical analysis of ranking data.
The contributors are drawn from a variety of fields including psychology, Cited by: Probability models and statistical analyses for ranking data. New York: Springer-Verlag, © (OCoLC) Material Type: Conference publication, Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors: Michael A Fligner; Joseph S Verducci.
Get this from a library. Probability Models and Statistical Analyses for Ranking Data. [Michael A Fligner; Joseph S Verducci] -- This book of edited contributions provides a wide-ranging survey of the use of probability models for ranking data and it introduces new methods for. In this paper several latent structure models for analyzing data that consist of complete or incomplete rankings are discussed.
First, attention is given to some latent class extensions of the Bradley-Terry-Luce model for ranking data. Next, various latent class models based Cited by: Statistics is the discipline that concerns the collection, organization, analysis, interpretation and presentation of data.
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This is the first of two books on the statistical theory of reliability and life testing. The present book concentrates on probabilistic aspects of reliability theory, while the forthcoming book will focus on inferential aspects of reliability and life testing, applying the probabilistic tools developed in this volume.
This book emphasizes the newer, research aspects of reliability theory. Models for Rank Data Introduction This chapter reviews a number of approaches to the statistical modeling of ranking data, dealing exclusively with complete rankings.
Chapter 2 reviews some methods for categorizing various models. Chapter 3 reviews likelihood and other methods for. Michael A. Fligner. Probability Models and Statistical Analyses for Ranking Data. Book. Jan ; Probability models and statistical analyses for ranking data. Papers presented at the AMS.
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An Analysis of Rank Ordered Data statistical test on n samples can be used to rank-order a list of alternatives and it is subjects to such a Simpson –kike paradox of aggregation.
In addition, Krusakal- Then the collection of such ranking makes up a data set. This book is dynamite: George E. Box, Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building It starts from zero knowledge of Statistics but it doesn't insult the reader's intelligence.
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An intrinsic aspect of reliability analysis is that the failure of components is best modelled using techniques drawn from probability and by:. Models on spheres and models for permutations. () In Probability Models and Statistical Analyses for Ranking Data. Springer Lecture Notes 80M. Fligner and J.
Verducci, editors. Matched pairs and ranked data. () (with J. Ye) In Probability Models and Statistical Analyses for Ranking Data.Most data fall into one of two groups: numerical or categorical.
Numerical data. These data have meaning as a measurement, such as a person’s height, weight, IQ, or blood pressure; or they’re a count, such as the number of stock shares a person owns, how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep.24 Uses of Statistical Modeling (Part I) Posted by Vincent Granville on Decem Methods for time series analyses may be divided into two classes: frequency-domain methods and time-domain methods.
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