Continuous Bivariate Distributions

Second Edition

  • Chin Diew Lai
  • N. Balakrishnan

Table of contents

  1. Front Matter
    Pages i-xxxiv
  2. N. Balakrishna, Chin Diew Lai
    Pages 1-32
  3. N. Balakrishna, Chin Diew Lai
    Pages 33-65
  4. N. Balakrishna, Chin Diew Lai
    Pages 67-103
  5. N. Balakrishna, Chin Diew Lai
    Pages 105-140
  6. N. Balakrishna, Chin Diew Lai
    Pages 141-177
  7. N. Balakrishna, Chin Diew Lai
    Pages 179-228
  8. N. Balakrishna, Chin Diew Lai
    Pages 229-278
  9. N. Balakrishna, Chin Diew Lai
    Pages 279-304
  10. N. Balakrishna, Chin Diew Lai
    Pages 305-350
  11. N. Balakrishna, Chin Diew Lai
    Pages 351-400
  12. N. Balakrishna, Chin Diew Lai
    Pages 401-475
  13. N. Balakrishna, Chin Diew Lai
    Pages 477-561
  14. N. Balakrishna, Chin Diew Lai
    Pages 563-590
  15. N. Balakrishna, Chin Diew Lai
    Pages 623-653
  16. Back Matter
    Pages 1-30

About this book

Introduction

Random variables are rarely independent in practice and so many multivariate distributions have been proposed in the literature to give a dependence structure for two or more variables. In this book, we restrict ourselves to the bivariate distributions for two reasons: (i) correlation structure and other properties are easier to understand and the joint density plot can be displayed more easily, and (ii) a bivariate distribution can normally be extended to a multivariate one through a vector or matrix representation. This volume is a revision of Chapters 1-17 of the previous book Continuous Bivariate Distributions, Emphasising Applications authored by Drs. Paul Hutchinson and Chin-Diew Lai.

The book updates the subject of copulas which have grown immensely during the past two decades. Similarly, conditionally specified distributions and skewed distributions have become important topics of discussion in this area of research. This volume, which provides an up-to-date review of various developments relating to bivariate distributions in general, should be of interest to academics and graduate students, as well as applied researchers in finance, economics, science, engineering and technology.

N. BALAKRISHNAN is Professor in the Department of Mathematics and Statistics at McMaster University, Hamilton, Ontario, Canada. He has published numerous research articles in many areas of probability and statistics and has authored a number of books including the four-volume series on Distributions in Statistics, jointly with Norman L. Johnson and S. Kotz, published by Wiley. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and the Editor-in-Chief of Communications in Statistics and the Executive Editor of Journal of Statistical Planning and Inference.

CHIN-DIEW LAI holds a Personal Chair in Statistics at Massey University, Palmerston North, New Zealand. He has published more than 100 peer-reviewed research articles and co-authored three well-received books. He was a former editor-in-chief and is now an Associate Editor of the Journal of Applied Mathematics and Decision Sciences.

 

 

Keywords

LDA Random variable correlation normal distribution

Authors and affiliations

  • Chin Diew Lai
    • 1
  • N. Balakrishnan
    • 2
  1. 1.Institute of Sciences and TechnologyMassey UniversityPalmerston NorthNew Zealand
  2. 2.Dept. Mathematics & StatisticsMcMaster UniversityHamiltonCanada

Bibliographic information

  • DOI https://doi.org/10.1007/b101765
  • Copyright Information Springer-Verlag New York 2009
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-09613-1
  • Online ISBN 978-0-387-09614-8
  • About this book