目　次
　

Chapter 1　Introduction
Chapter 2　Modeling Concepts and Methods
Chapter 3　The Smoothness Priors Concept
Chapter 4　Scalar Least Squares Modeling
Chapter 5　Linear Gaussian State Space Modeling
Chapter 6　General State Space Modeling
Chapter 7　Applications of Linear Gaussian State
Space Modeling
Chapter 8　Modeling Trends
Chapter 9　Seasonal Adjustment
Chapter 10　Estimation of Time Varying Variance
Chapter 11　Modeling Scalar Nonstationary Covariance Time Series
Chapter 12　Modeling Multivariate Nonstationary Covariance Time Series
Chapter 13　Modeling Inhomogeneous Discrete Processes
Chapter 14　Quasi-Periodic Process Modeling
Chapter 15　Nonlinear Smoothing
Chapter 16　Other Applications