Nonparametric Estimation of Conditional Medians for Linear and Related Processes
We 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.
|Length:||31,  p.|
|Date of creation:||Oct 2007|
|Date of revision:|
|Note:||September 2005; October 2007 (revised)|
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Web page: http://www.econ.hit-u.ac.jp/
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- Honda, Toshio, 2006.
"Nonparametric Density Estimation for Linear Processes with Infinite Variance,"
2005-13, Graduate School of Economics, Hitotsubashi University.
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