The KDE procedure performs either univariate or bivariate kernel density estimation. Statistical density estimation involves approximating a hypothesized probability density function from observed ...
Transformation from a parametric family can improve the performance of kernel density estimation. In this article we give two data-driven estimators for the optimal transformation parameter. We ...
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those ...
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