of the exchange rate. As non-linear alternative, a Kernel regression was best able to explain volatile exchange rate …

(n)) coverage error. Asymptotic power is shown to be optimal. Using kernel smoothing, we propose a related method for nonparametric …

Standard kernel density estimation methods are very often used in practice to estimate density function. It works well … logarithmic transformation of the data, combined with standard kernel density estimation methods, can provide a much better fit of …

-convolution kernel estimator for the location and size of regression discontinuities. We also propose a bootstrapping procedure for …

This paper addresses the following question: How much information do the kernel function and the bandwidth provide for … nonparametric kernel estimation? The question is addressed by showing that kernel estimation of a cumulative distribution function … smooth estimate. The transmission channel is the kernel function itself, which is a conditional distribution with a data …

This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of …

. Through the Kernel Density Function and local indicators of spatial autocorrelation analysis, this paper finds that housing …