Johnson / Kemp / Kotz | Univariate Discrete Distributions, 3e Set | Buch | 978-0-470-38337-7 | www.sack.de

Buch, Englisch, 3256 Seiten, Format (B × H): 163 mm x 236 mm, Gewicht: 612 g

Johnson / Kemp / Kotz

Univariate Discrete Distributions, 3e Set


3rd Revised Auflage
ISBN: 978-0-470-38337-7
Verlag: Wiley

Buch, Englisch, 3256 Seiten, Format (B × H): 163 mm x 236 mm, Gewicht: 612 g

ISBN: 978-0-470-38337-7
Verlag: Wiley


This Set Contains:

Continuous Multivariate Distributions, Volume 1, Models and Applications, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson
Continuous Univariate Distributions, Volume 1, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson
Continuous Univariate Distributions, Volume 2, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson
Discrete Multivariate Distributions by Samuel Kotz, N. Balakrishnan and Normal L. Johnson
Univariate Discrete Distributions, 3rd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson

Discover the latest advances in discrete distributions theory

The Third Edition of the critically acclaimed Univariate Discrete Distributions provides a self-contained, systematic treatment of the theory, derivation, and application of probability distributions for count data. Generalized zeta-function and q-series distributions have been added and are covered in detail. New families of distributions, including Lagrangian-type distributions, are integrated into this thoroughly revised and updated text. Additional applications of univariate discrete distributions are explored to demonstrate the flexibility of this powerful method.

A thorough survey of recent statistical literature draws attention to many new distributions and results for the classical distributions. Approximately 450 new references along with several new sections are introduced to reflect the current literature and knowledge of discrete distributions.

Beginning with mathematical, probability, and statistical fundamentals, the authors provide clear coverage of the key topics in the field, including:

- Families of discrete distributions
- Binomial distribution
- Poisson distribution
- Negative binomial distribution
- Hypergeometric distributions
- Logarithmic and Lagrangian distributions
- Mixture distributions
- Stopped-sum distributions
- Matching, occupancy, runs, and q-series distributions
- Parametric regression models and miscellanea

Emphasis continues to be placed on the increasing relevance of Bayesian inference to discrete distribution, especially with regard to the binomial and Poisson distributions. New derivations of discrete distributions via stochastic processes and random walks are introduced without unnecessarily complex discussions of stochastic processes. Throughout the Third Edition, extensive information has been added to reflect the new role of computer-based applications.

With its thorough coverage and balanced presentation of theory and application, this is an excellent and essential reference for statisticians and mathematicians.

Johnson / Kemp / Kotz Univariate Discrete Distributions, 3e Set jetzt bestellen!

Weitere Infos & Material


Preface xvii

1 Preliminary Information 1

2 Families of Discrete Distributions 74

3 Binomial Distribution 108

4 Poisson Distribution 156

5 Negative Binomial Distribution 208

6 Hypergeometric Distributions 251

7 Logarithmic and Lagrangian Distributions 302

8 Mixture Distributions 343

9 Stopped-Sum Distributions 381

10 Matching, Occupancy, Runs, and q-Series Distributions 430

11 Parametric Regression Models and Miscellanea 478

Bibliography 535

Abbreviations 631

Index 633


NORMAN L. JOHNSON, PHD, was Professor Emeritus, Department of Statistics, University of North Carolina at Chapel Hill. Dr. Johnson was Editor-in-Chief (with Dr. Kotz) of the Encyclopedia of Statistical Sciences, Second Edition (Wiley).

ADRIENNE W. KEMP, PHD, is Honorary Senior Lecturer at the Mathematical Institute, University of St. Andrews in Scotland.

SAMUEL KOTZ, PHD, is Professor and Research Scholar, Department of Engineering Management and Systems Engineering, The George Washington University in Washington, DC.



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