The Inverse Gaussian Distribution

Statistical Theory and Applications

  • V.¬†Seshadri

Part of the Lecture Notes in Statistics book series (LNS, volume 137)

Table of contents

  1. Front Matter
    Pages n1-xii
  2. Statistical Theory

    1. V. Seshadri
      Pages 1-22
    2. V. Seshadri
      Pages 23-37
    3. V. Seshadri
      Pages 38-72
    4. V. Seshadri
      Pages 73-91
    5. V. Seshadri
      Pages 92-113
    6. V. Seshadri
      Pages 114-120
    7. V. Seshadri
      Pages 121-166
  3. Applications

    1. V. Seshadri
      Pages 167-171
    2. V. Seshadri
      Pages 172-190
    3. V. Seshadri
      Pages 191-193
    4. V. Seshadri
      Pages 194-197
    5. V. Seshadri
      Pages 198-202
    6. V. Seshadri
      Pages 203-205
    7. V. Seshadri
      Pages 206-219
    8. V. Seshadri
      Pages 220-229
    9. V. Seshadri
      Pages 230-231
    10. V. Seshadri
      Pages 232-234
    11. V. Seshadri
      Pages 235-251
    12. V. Seshadri
      Pages 252-258
    13. V. Seshadri
      Pages 259-261
    14. V. Seshadri
      Pages 262-264
    15. V. Seshadri
      Pages 265-283
    16. V. Seshadri
      Pages 284-285
    17. V. Seshadri
      Pages 286-297
    18. V. Seshadri
      Pages 298-304
    19. V. Seshadri
      Pages 305-308
    20. V. Seshadri
      Pages 309-313
    21. V. Seshadri
      Pages 314-316
  4. Back Matter
    Pages 317-349

About this book


This book is written in the hope that it will serve as a companion volume to my first monograph. The first monograph was largely devoted to the probabilistic aspects of the inverse Gaussian law and therefore ignored the statistical issues and related data analyses. Ever since the appearance of the book by Chhikara and Folks, a considerable number of publications in both theory and applications of the inverse Gaussian law have emerged thereby justifying the need for a comprehensive treatment of the issues involved. This book is divided into two sections and fills up the gap updating the material found in the book of Chhikara and Folks. Part I contains seven chapters and covers distribution theory, estimation, significance tests, goodness-of-fit, sequential analysis and compound laws and mixtures. The first part forms the backbone of the theory and wherever possible I have provided illustrative examples for easy assimilation of the theory. The second part is devoted to a wide range of applications from various disciplines. The applied statistician will find numerous instances of examples which pertain to a first passage time situation. It is indeed remarkable that in the fields of life testing, ecology, entomology, health sciences, traffic intensity and management science the inverse Gaussian law plays a dominant role. Real life examples from actuarial science and ecology came to my attention after this project was completed and I found it impossible to include them.


Area Gaussian distribution Mathematica Meteor Statistica Survival analysis demography distribution ecology management modeling normal distribution physiology reliability remote sensing

Authors and affiliations

  • V.¬†Seshadri
    • 1
  1. 1.Department of Mathematics and StatisticsMcGill UniversityMontrealCanada

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York, Inc. 1999
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98618-0
  • Online ISBN 978-1-4612-1456-4
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site