000 | 01345nam a22001817a 4500 | ||
---|---|---|---|
005 | 20240207103330.0 | ||
008 | 240207b |||||||| |||| 00| 0 eng d | ||
020 | _a9789811607134 | ||
082 |
_a519.550243 _bHAG |
||
100 |
_aHagiwara, Junichiro _913993 |
||
245 | _aTime series analysis for the state-space model with R/Stan | ||
260 |
_bSpringer _aSwitzerland _c2021 |
||
300 | _axiii, 247 p. | ||
365 |
_aEURO _b129.99 |
||
520 | _aThis book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader’s analytical capability. | ||
650 |
_aTime Series Analysis _915206 |
||
942 |
_cBK _2ddc |
||
999 |
_c5726 _d5726 |