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.

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.

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.

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 relevanc…