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Bayesian Inference with Geodetic Applications

  • Authors
  • Karl-Rudolf Koch

Part of the Lecture Notes in Earth Sciences book series (LNEARTH, volume 31)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Karl-Rudolf Koch
    Pages 1-2
  3. Karl-Rudolf Koch
    Pages 3-3
  4. Karl-Rudolf Koch
    Pages 4-8
  5. Karl-Rudolf Koch
    Pages 9-32
  6. Karl-Rudolf Koch
    Pages 33-36
  7. Karl-Rudolf Koch
    Pages 37-39
  8. Karl-Rudolf Koch
    Pages 40-48
  9. Karl-Rudolf Koch
    Pages 49-51
  10. Karl-Rudolf Koch
    Pages 52-60
  11. Karl-Rudolf Koch
    Pages 61-61
  12. Karl-Rudolf Koch
    Pages 62-98
  13. Karl-Rudolf Koch
    Pages 99-108
  14. Karl-Rudolf Koch
    Pages 109-121
  15. Karl-Rudolf Koch
    Pages 135-143
  16. Karl-Rudolf Koch
    Pages 156-167
  17. Back Matter
    Pages 169-198

About this book

Introduction

This introduction to Bayesian inference places special emphasis on applications. All basic concepts are presented: Bayes' theorem, prior density functions, point estimation, confidence region, hypothesis testing and predictive analysis. In addition, Monte Carlo methods are discussed since the applications mostly rely on the numerical integration of the posterior distribution. Furthermore, Bayesian inference in the linear model, nonlinear model, mixed model and in the model with unknown variance and covariance components is considered. Solutions are supplied for the classification, for the posterior analysis based on distributions of robust maximum likelihood type estimates, and for the reconstruction of digital images.

Keywords

Likelihood Monte Carlo integration Monte-Carlo Methode Predictive Anasysis Prior distribution Priori-Verteilung Variance gemischte Modelle lineare Modelle prädiktive Analyse

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0048699
  • Copyright Information Springer-Verlag Berlin Heidelberg 1990
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-53080-0
  • Online ISBN 978-3-540-46601-7
  • Series Print ISSN 0930-0317
  • Series Online ISSN 1613-2580
  • Buy this book on publisher's site