Nonparametric estimation of conditional medians for linear and related processes
AbstractWe consider nonparametric estimation of conditional medians for time series data. The time series data are generated from two mutually independent linear processes. The linear processes may show long-range dependence.The estimator of the conditional medians is based on minimizing the locally weighted sum of absolute deviations for local linear regression. We present the asymptotic distribution of the estimator. The rate of convergence is independent of regressors in our setting. The result of a simulation study is also given.
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Bibliographic InfoArticle provided by Springer in its journal Annals of the Institute of Statistical Mathematics.
Volume (Year): 62 (2010)
Issue (Month): 6 (December)
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Web page: http://www.springerlink.com/link.asp?id=102845
Other versions of this item:
- Honda, Toshio, 2007. "Nonparametric Estimation of Conditional Medians for Linear and Related Processes," Discussion Papers 2005-04, Graduate School of Economics, Hitotsubashi University.
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