Estimation of multiple-regime regressions with least absolutes deviation
This paper considers least absolute deviations estimation of a regression model with multiple change points occurring at unknown times. Some asymptotic results, including rates of convergence and asymptotic distributions, for the estimated change points and the estimated regression coefficient are derived. Results are obtained without assuming that each regime spans a positive fraction of the sample size. In addition, the number of change points is allowed to grow as the sample size increases. Estimation of the number of change points is also considered. A feasible computational algorithm is developed. An application is also given, along with some monte carlo simulations.
|Date of creation:||Feb 1995|
|Date of revision:||Feb 1998|
|Publication status:||Published in Journal of Statistical Planning and Inference 1.74(1998): pp. 103-134|
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Web page: https://mpra.ub.uni-muenchen.de
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