Table of Contents
- Chapter 1: The Subjective Interpretation of Probability
- Chapter 2: Bayesian Inference
- Chapter 3: Point Estimation
- Chapter 4: Frequentist Properties of Bayesian Estimators
- Chapter 5: Interval Estimation
- Chapter 6: Hypothesis Testing
- Chapter 7: Prediction
- Chapter 8: Choice of Prior
- Chapter 9: Asymptotic Bayes
- Chapter 10: The Linear Regression Model
- Chapter 11: Basics of Bayesian Computation
- Chapter 12: Hierarchical Models
- Chapter 13: The Linear Regression Model with General Error Covariance Matrix
- Chapter 14: Latent Variable Models
- Chapter 15: Mixture Models
- Chapter 16: Bayesian Model Averaging
and Selection
- Chapter 17: Some Stationary Time Series Models
- Chapter 18: Some Nonstationary Time Series Models