Bayesian Inference for Partially Identified Models

Bayesian Inference for Partially Identified Models

by Paul Gustafson
Released April 2015
Publisher(s): Chapman and Hall/CRC
ISBN: 9781439869406

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Book description

This book shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. He covers a range of PIMs, including models for misclassified data and models involving instrumental variables. He also includes real data applications of PIMs that have recently appeared in the literature.

Table of contents

  1. Cover (1/2)
  2. Cover (2/2)
  3. Dedication
  4. Contents
  5. List of Figures
  6. List of Tables
  7. Preface
  8. Guide to Notation
  9. Chapter 1: Introduction (1/3)
  10. Chapter 1: Introduction (2/3)
  11. Chapter 1: Introduction (3/3)
  12. Chapter 2: The Structure of Inference in Partially Identified Models (1/8)
  13. Chapter 2: The Structure of Inference in Partially Identified Models (2/8)
  14. Chapter 2: The Structure of Inference in Partially Identified Models (3/8)
  15. Chapter 2: The Structure of Inference in Partially Identified Models (4/8)
  16. Chapter 2: The Structure of Inference in Partially Identified Models (5/8)
  17. Chapter 2: The Structure of Inference in Partially Identified Models (6/8)
  18. Chapter 2: The Structure of Inference in Partially Identified Models (7/8)
  19. Chapter 2: The Structure of Inference in Partially Identified Models (8/8)
  20. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (1/6)
  21. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (2/6)
  22. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (3/6)
  23. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (4/6)
  24. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (5/6)
  25. Chapter 3: Partial Identification versus Model Misspecification: Is Honesty Best? (6/6)
  26. Chapter 4: Further Examples: Models Involving Misclassification (1/6)
  27. Chapter 4: Further Examples: Models Involving Misclassification (2/6)
  28. Chapter 4: Further Examples: Models Involving Misclassification (3/6)
  29. Chapter 4: Further Examples: Models Involving Misclassification (4/6)
  30. Chapter 4: Further Examples: Models Involving Misclassification (5/6)
  31. Chapter 4: Further Examples: Models Involving Misclassification (6/6)
  32. Chapter 5: Further Examples: Models Involving Instrumental Variables (1/4)
  33. Chapter 5: Further Examples: Models Involving Instrumental Variables (2/4)
  34. Chapter 5: Further Examples: Models Involving Instrumental Variables (3/4)
  35. Chapter 5: Further Examples: Models Involving Instrumental Variables (4/4)
  36. Chapter 6: Further Examples (1/4)
  37. Chapter 6: Further Examples (2/4)
  38. Chapter 6: Further Examples (3/4)
  39. Chapter 6: Further Examples (4/4)
  40. Chapter 7: Further Topics (1/4)
  41. Chapter 7: Further Topics (2/4)
  42. Chapter 7: Further Topics (3/4)
  43. Chapter 7: Further Topics (4/4)
  44. Chapter 8: Concluding Thoughts (1/2)
  45. Chapter 8: Concluding Thoughts (2/2)
  46. Bibliography (1/3)
  47. Bibliography (2/3)
  48. Bibliography (3/3)

Product information

  • Title: Bayesian Inference for Partially Identified Models
  • Author(s): Paul Gustafson
  • Release date: April 2015
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781439869406