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The Analysis of Stochastic Processes using GLIM

  • James K. Lindsey

Part of the Lecture Notes in Statistics book series (LNS, volume 72)

Table of contents

  1. Front Matter
    Pages I-VI
  2. James K. Lindsey
    Pages 1-20
  3. James K. Lindsey
    Pages 21-42
  4. James K. Lindsey
    Pages 43-78
  5. James K. Lindsey
    Pages 79-102
  6. James K. Lindsey
    Pages 103-113
  7. James K. Lindsey
    Pages 114-132
  8. James K. Lindsey
    Pages 133-154
  9. James K. Lindsey
    Pages 155-188
  10. Back Matter
    Pages 206-294

About this book

Introduction

The aim of this book is to present a survey of the many ways in which the statistical package GLIM may be used to model and analyze stochastic processes. Its emphasis is on using GLIM interactively to apply statistical techniques, and examples are drawn from a wide range of applications including medicine, biology, and the social sciences. It is based on the author's many years of teaching courses along these lines to both undergraduate and graduate students. The author assumes that readers have a reasonably strong background in statistics such as might be gained from undergraduate courses and that they are also familiar with the basic workings of GLIM. Topics covered include: the analysis of survival data, regression and fitting distributions, time series analysis (including both the time and frequency domains), repeated measurements, and generalized linear models.

Keywords

Fitting Gaussian distribution Generalized linear model Normal distribution Regression analysis Time series Variance Weibull distribution analysis of variance best fit correlation linear regression

Authors and affiliations

  • James K. Lindsey
    • 1
  1. 1.Faculté d’Economie, de Gestion et de Sciences SocialesUniversité de LiègeLiègeBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-2888-2
  • Copyright Information Springer-Verlag New York 1992
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-97761-4
  • Online ISBN 978-1-4612-2888-2
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site
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