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Optimal convergence rates of nonparametric conditional quantiles in dependent cases

Optimal convergence rates of nonparametric conditional quantiles in dependent cases
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摘要 The ordinary quantiles for univariate data were successfully generalized to linear modelsin Koenker and Bassett. Regression quantiles provide more specific and more global in-formation on the relationship of two variables through their distributions. Mosteller andTukey argued that the use of regression quantiles helps to provide a more complete pic-
出处 《Chinese Science Bulletin》 SCIE EI CAS 1995年第8期627-631,共5页
基金 Project supported in part by a postdoctoral fellowship and the National Natural Science Foundation of China.
关键词 NONPARAMETRIC regression QUANTILES B-SPLINES optimal rates of convergence STRICTLY STATIONARY sequence β-mixing. NONPARAMETRIC REGRESSION QUANTILES B-SPLINES OPTIMAL RATES OF CONVERGENCE STRICTLY STATIONARY SEQUENCE BETA-MIXING
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