Weakly universally consistent static forecasting of stationary and ergodic time series via local averaging and least squares estimates
| Autor: | Daniel Jones, Michael Kohler, Tina Felber, Harro Walk |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Statistics and Probability
Variables Series (mathematics) Mean squared error Applied Mathematics media_common.quotation_subject Zero (complex analysis) Conditional expectation Least squares Square-integrable function Statistics Ergodic theory Applied mathematics Statistics Probability and Uncertainty Mathematics media_common |
| Zdroj: | Journal of Statistical Planning and Inference. 143:1689-1707 |
| ISSN: | 0378-3758 |
| Popis: | Given a stationary and ergodic time series the problem of estimating the conditional expectation of the dependent variable at time zero given the infinite past is considered. It is shown that the mean squared error of a combination of suitably defined local averaging or least squares estimates converges to zero for all distributions whenever the dependent variable is square integrable. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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