Multivariate Density Estimation Using a Multivariate Weighted Log-Normal Kernel
Gaku Igarashi ()
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Gaku Igarashi: University of Tsukuba
Sankhya A: The Indian Journal of Statistics, 2018, vol. 80, issue 2, 247-266
Abstract This paper suggests a multivariate asymmetric kernel density estimation using a multivariate weighted log-normal (LN) kernel for non-negative multivariate data. Asymptotic properties of the multivariate weighted LN kernel density estimator are studied. Simulation studies are also conducted in the bivariate situation.
Keywords: Nonparametric density estimation; Boundary problem; Asymmetric kernel; Multivariate log-normal density; Primary 62G07; Secondary 62G20 (search for similar items in EconPapers)
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