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Unobserved Variables

Models and Misunderstandings

  • David J. Bartholomew

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Table of contents

  1. Front Matter
    Pages i-vii
  2. David J. Bartholomew
    Pages 1-7
  3. David J. Bartholomew
    Pages 9-12
  4. David J. Bartholomew
    Pages 13-19
  5. David J. Bartholomew
    Pages 21-27
  6. David J. Bartholomew
    Pages 29-32
  7. David J. Bartholomew
    Pages 33-37
  8. David J. Bartholomew
    Pages 39-46
  9. David J. Bartholomew
    Pages 47-53
  10. David J. Bartholomew
    Pages 55-60
  11. David J. Bartholomew
    Pages 61-67
  12. David J. Bartholomew
    Pages 69-76
  13. David J. Bartholomew
    Pages 77-82
  14. David J. Bartholomew
    Pages 83-86

About this book

Introduction

​The classical statistical problem typically involves a probability distribution which depends on a number of unknown parameters. The form of the distribution may be known, partially or completely, and inferences have to be made on the basis of a sample of observations drawn from the distribution; often, but not necessarily, a random sample. This brief deals with problems where some of the sample members are either unobserved or hypothetical, the latter category being introduced as a means of better explaining the data. Sometimes we are interested in these kinds of variable themselves and sometimes in the parameters of the distribution. Many problems that can be cast into this form are treated. These include: missing data, mixtures, latent variables, time series and social measurement problems. Although all can be accommodated within a Bayesian framework, most are best treated from first principles.

Keywords

Bayesian methods Latent variables Missing data Mixtures Time Series

Authors and affiliations

  • David J. Bartholomew
    • 1
  1. 1.London School of EconomicsLondonUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-39912-1
  • Copyright Information The Author(s) 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-642-39911-4
  • Online ISBN 978-3-642-39912-1
  • Series Print ISSN 2191-544X
  • Series Online ISSN 2191-5458
  • Buy this book on publisher's site