Statistical Modelling

Proceedings of GLIM 89 and the 4th International Workshop on Statistical Modelling held in Trento, Italy, July 17–21, 1989

  • Adriano Decarli
  • Brian J. Francis
  • Robert Gilchrist
  • Gilg U. H. Seeber

Part of the Lecture Notes in Statistics book series (LNS, volume 57)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Papers Presented in the Glim Working Party Session

    1. Michael Clarke, Robert Gilchrist, Anthony Scallan, Mel Slater
      Pages 6-17
    2. Mick Green, Brian Francis, Malcolm Bradley
      Pages 18-25
    3. Carl M. O’Brien
      Pages 37-43
  3. Invited and Contributed Papers

About these proceedings

Introduction

This volume constitutes the Proceedings of the joint meeting of GLIM89 and the 4th International Workshop on statistical Modelling, held in Trento, Italy, from 17 to 21 July 1989. The meeting aimed to bring together researchers interested in the development and application of generalized linear modelling in GLIM and those interested in statistical modelling in its widest sense. This joint meeting built upon the success of previous workshops held in Innsbruck, perugia and Vienna, and upon the two previous GLIM conferences , GLIM82 and GLIM85. The Proceedings of the latter two being available as numbers 14 and 32 in the springer Verlag series of Lecture Notes in Statistics). Much statistical modelling is carried out using GLIM, as is apparent from many of the papers in these Proceedings; however, the Programme Committee were also keen on encouraging papers which discussed more general modelling techniques. Thus about a third of the papers in this volume are outside the GLIM framework. The Programme Committee specifically requested non-theoretical papers in addition to considering theoretical contributions. Thus there are papers in a wide range of practical areas, such as radio spectral occupancy, comparison of birthweights, intervals between births, accidents of railway workers, genetics, demography, medical trials, the social sciences and insurance. A wide range of theoretical developments are discussed, for example, overdispersion, non-exponential family modelling, novel approaches to analysing contingency tables, random effects models, Kalman Filtering, model checking and extensions of Wedderburn's theoretical underpinning of GLMs.

Keywords

Fitting Generalized linear model Likelihood algorithms best fit linear regression

Editors and affiliations

  • Adriano Decarli
    • 1
  • Brian J. Francis
    • 2
  • Robert Gilchrist
    • 3
  • Gilg U. H. Seeber
    • 4
  1. 1.Istituto di Biometria e Statistica MedicaMilanoItaly
  2. 2.Centre for Applied StatisticsFylde College, Lancaster UniversityLancasterUK
  3. 3.Polytechnic of North LondonLondonUK
  4. 4.Insitut für StatistikUniversität InnsbruckInnsbruckAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-3680-1
  • Copyright Information Springer-Verlag New York 1989
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-97097-4
  • Online ISBN 978-1-4612-3680-1
  • Series Print ISSN 0930-0325
  • About this book