Nonparametric M-estimation with long-memory errors

Jan Beran, Sucharita Ghosh and Philipp Sibbertsen

No 2000,36, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind this study is illustrated with an example.

Date: 2000
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Working Paper: Nonparametric M-Estimation with Long-Memory Errors (2000)
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