Bivariate density estimation using normal-gamma kernel with application to astronomy

01/25/2018

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by   Uttam Bandyopadhyay, et al.

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We consider the problem of estimation of a bivariate density function with support ×[0,∞), where a classical bivariate kernel estimator causes boundary bias due to the non-negative variable. To overcome this problem, we propose four kernel density estimators whose performances are compared in terms of the mean integrated squared error. Simulation study shows that the estimator based on our proposed normal-gamma (NG) kernel performs best, whose applicability is demonstrated using two astronomical data sets.