On alternative state space representations of time series models
β Scribed by Masanao Aoki
- Publisher
- Elsevier Science
- Year
- 1988
- Tongue
- English
- Weight
- 691 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0165-1889
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract This paper discusses two alternative innovation representations (forward and backward) of a state space model of a multivariate weakly stationary time series, and suggests estimators of system matrices and innovation noise covariances which are alternative to these based on stochastic r
State-space models with exponential and conjugate exponential family densities are introduced. Examples include Poisson-Gamma, Binomial-Beta, Gamma-Gamma and Normal-Normal processes. Maximum likelihood and quasilikelihood estimators and their properties are discussed. Results from a simulation study