论文信息 - Varying kernel density estimation on R

Varying kernel density estimation on R

In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated. Simulation studies are conducted to compare a new estimator and its modified version with traditional kernel density construction.

Robert M. Mnatsakanov | Khachatur Sarkisian | R. Mnatsakanov | Khachatur Sarkisian

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