Inferential Models

Inferential Models

by Ryan Martin, Chuanhai Liu
Released September 2015
Publisher(s): Chapman and Hall/CRC
ISBN: 9781439886519

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Book description

This book introduces the authors' recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The book covers the foundational motivations for this new approach, the basic theory behind its calibration properties, many important applications, and new directions for research. It explores a new way of thinking compared to existing schools of thought on statistical inference and encourages readers to think carefully about the correct approach to scientific inference.

Table of contents

  1. Cover (1/2)
  2. Cover (2/2)
  3. Dedication
  4. Contents (1/2)
  5. Contents (2/2)
  6. Preface
  7. Chapter 1: Preliminaries (1/5)
  8. Chapter 1: Preliminaries (2/5)
  9. Chapter 1: Preliminaries (3/5)
  10. Chapter 1: Preliminaries (4/5)
  11. Chapter 1: Preliminaries (5/5)
  12. Chapter 2: Prior-Free Probabilistic Inference (1/4)
  13. Chapter 2: Prior-Free Probabilistic Inference (2/4)
  14. Chapter 2: Prior-Free Probabilistic Inference (3/4)
  15. Chapter 2: Prior-Free Probabilistic Inference (4/4)
  16. Chapter 3: Two Fundamental Principles (1/2)
  17. Chapter 3: Two Fundamental Principles (2/2)
  18. Chapter 4: Inferential Models (1/6)
  19. Chapter 4: Inferential Models (2/6)
  20. Chapter 4: Inferential Models (3/6)
  21. Chapter 4: Inferential Models (4/6)
  22. Chapter 4: Inferential Models (5/6)
  23. Chapter 4: Inferential Models (6/6)
  24. Chapter 5: Predictive Random Sets (1/6)
  25. Chapter 5: Predictive Random Sets (2/6)
  26. Chapter 5: Predictive Random Sets (3/6)
  27. Chapter 5: Predictive Random Sets (4/6)
  28. Chapter 5: Predictive Random Sets (5/6)
  29. Chapter 5: Predictive Random Sets (6/6)
  30. Chapter 6: Conditional Inferential Models (1/4)
  31. Chapter 6: Conditional Inferential Models (2/4)
  32. Chapter 6: Conditional Inferential Models (3/4)
  33. Chapter 6: Conditional Inferential Models (4/4)
  34. Chapter 7: Marginal Inferential Models (1/4)
  35. Chapter 7: Marginal Inferential Models (2/4)
  36. Chapter 7: Marginal Inferential Models (3/4)
  37. Chapter 7: Marginal Inferential Models (4/4)
  38. Chapter 8: Normal Linear Models (1/4)
  39. Chapter 8: Normal Linear Models (2/4)
  40. Chapter 8: Normal Linear Models (3/4)
  41. Chapter 8: Normal Linear Models (4/4)
  42. Chapter 9: Prediction of Future Observations (1/4)
  43. Chapter 9: Prediction of Future Observations (2/4)
  44. Chapter 9: Prediction of Future Observations (3/4)
  45. Chapter 9: Prediction of Future Observations (4/4)
  46. Chapter 10: Simultaneous Inference on Multiple Assertions (1/4)
  47. Chapter 10: Simultaneous Inference on Multiple Assertions (2/4)
  48. Chapter 10: Simultaneous Inference on Multiple Assertions (3/4)
  49. Chapter 10: Simultaneous Inference on Multiple Assertions (4/4)
  50. Chapter 11: Generalized Inferential Models (1/6)
  51. Chapter 11: Generalized Inferential Models (2/6)
  52. Chapter 11: Generalized Inferential Models (3/6)
  53. Chapter 11: Generalized Inferential Models (4/6)
  54. Chapter 11: Generalized Inferential Models (5/6)
  55. Chapter 11: Generalized Inferential Models (6/6)
  56. Chapter 12: Future Research Topics (1/2)
  57. Chapter 12: Future Research Topics (2/2)
  58. Bibliography (1/4)
  59. Bibliography (2/4)
  60. Bibliography (3/4)
  61. Bibliography (4/4)
  62. Back Cover

Product information

  • Title: Inferential Models
  • Author(s): Ryan Martin, Chuanhai Liu
  • Release date: September 2015
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781439886519