Probability and Bayesian Statistics

  • R. Viertl

Table of contents

  1. Front Matter
    Pages i-xii
  2. R. E. Barlow, R. W. Mensing, N. G. Smiriga
    Pages 17-30
  3. Asit Basu, Ghasem Tarmast
    Pages 31-38
  4. M. J. Bayarri, M. H. DeGroot
    Pages 39-51
  5. Francesco Carlucci, Gino Zornitta
    Pages 73-82
  6. Robert T. Clemen, Robert L. Winkler
    Pages 97-110
  7. Guido Consonni, Piero Veronese
    Pages 111-120
  8. N. R. Draper, I. Guttman
    Pages 139-150
  9. Ian R. Dunsmore, Richard J. Boys
    Pages 151-158
  10. Klaus Felsenstein
    Pages 169-174
  11. Dani Gamerman
    Pages 183-192

About this book

Introduction

This book contains selected and refereed contributions to the "Inter­ national Symposium on Probability and Bayesian Statistics" which was orga­ nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa­ pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub­ jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics and stochastic processes, to real applications in economics, reliability and hydrology. Also the question is raised if it is necessary to develop new techniques to model and analyze fuzzy observations in samples. The articles are arranged in alphabetical order according to the family name of the first author of each paper to avoid a hierarchical ordering of importance of the different topics. Readers interested in special topics can use the index at the end of the book as guide.

Keywords

Maxima Time series Variance bayesian statistics linear regression probability programming time

Editors and affiliations

  • R. Viertl
    • 1
  1. 1.Technical University of ViennaViennaAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4613-1885-9
  • Copyright Information Springer-Verlag US 1987
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-9050-6
  • Online ISBN 978-1-4613-1885-9
  • About this book