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The ARIMA model in state space form
| Content Provider | Semantic Scholar |
|---|---|
| Author | Jong, Pieter De Penzer, Jeremy |
| Copyright Year | 2000 |
| Abstract | This article explores an alternative state space representation for ARIMA models to that usually advocated. The alternative representation has minimal state order. More importantly, it has more convenient Kalman filter convergence properties. This convergence reveals the concrete connection between classical infinite sample representations based on lag polynomials and the recursive Kalman filter construction. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.lse.ac.uk/collections/statistics/documents/researchreport40.pdf |
| Alternate Webpage(s) | http://www2.lse.ac.uk/statistics/documents/researchreport40.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Autoregressive integrated moving average Computation (action) Convergence (action) Kalman filter Polynomial Recursion Smoothing (statistical technique) State space State-space representation Time series |
| Content Type | Text |
| Resource Type | Article |
