| Autor: |
Brodsky, Boris, Darkhovsky, Boris |
| Rok vydání: |
2011 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
In this paper the problem of retrospective change-point detection and estimation in multivariate linear models is considered. The lower bounds for the error of change-point estimation are proved in different cases (one change-point: deterministic and stochastic predictors, multiple change-points). A new method for retrospective change-point detection and estimation is proposed and its main performance characteristics (type 1 and type 2 errors, the error of estimation) are studied for dependent observations in situations of deterministic and stochastic predictors and unknown change-points. We prove that this method is asymptotically optimal by the order of convergence of change-point estimates to their true values as the sample size tends to infinity. Results of a simulation study of the main performance characteristics of proposed method in comparison with other well known methods of retrospective change-point detection and estimation are presented. |
| Databáze: |
arXiv |
| Externí odkaz: |
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