State-space methods for time series analysis : theory, applications and software

✍ Scribed by Casals, Jose

Publisher: CRC Press
Year: 2016
Tongue: English
Leaves: 290
Series: Monographs on statistics and applied probability (Series) 149
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Content: 1. Introduction --
2. Linear state-space models --
3. Model transformations --
4. Filtering and smoothing --
5. Likelihood computation for fixed-coefficients models --
6. The likelihood of models with varying parameters --
7. Subspace methods --
8. Signal extraction --
9. The VARMAX representation of a state-space model --
10. Aggregation and disaggregation of time series --
11. Cross-sectional extension : longitudinal and panel data.

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