Title: Multivariate Density Estimation Using a Multivariate Weighted Log-Normal Kernel
Author(s): Gaku Igarashi
Pages: 247 -- 266
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.