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When has estimation reached a steady state? The Bayesian sequential test
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kárný, Miroslav Kracík, Jan Nagy, Ivan Nedoma, Petr |
| Copyright Year | 2005 |
| Abstract | SUMMARY Thispaperisconcernedwithdistributionsoftimeseries,which(i)arein∞uencedbyinitialconditions (ii) are stimulated by an exogenous signal or (iii) are obtained by recursive estimation of underlying parametersandthusundergoatransientperiod. In computer intensive applications, it is desirable to stop the processing when the transient period is practically over. This aspect is addressed here from a Bayesian perspective. Under an often met assumption that the model of a system’s time series is recursively estimated anyway, the computational overhead of the constructed stopping rule is negligible. Algorithmic details are presented for important normal ARX models (auto-regression with exogenous variable) and models ofdiscrete-valued,independent,identicallydistributeddata.Thelattercaseprovidesnon-parametric Bayesian estimation of credibility interval with sequential stopping. Copyright c ∞ 2004 John Wiley & Sons,Ltd. |
| Starting Page | 41 |
| Ending Page | 57 |
| Page Count | 17 |
| File Format | PDF HTM / HTML |
| DOI | 10.1002/acs.831 |
| Volume Number | 19 |
| Alternate Webpage(s) | http://library.utia.cas.cz/prace/20050015.pdf |
| Alternate Webpage(s) | https://doi.org/10.1002/acs.831 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
