This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, in non-uniform designs. We further find that...

This note derives the general form of the approximate mean integrated squared error for the q-variate, th-order kernel density r th derivative estimator. This formula allows for normal reference rule-of-thumb bandwidths to be derived. We give tables for some of the most common cases in the...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, ‘partial mean’ plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A...

Uncovering gradients is of crucial importance across a broad range of economic environments. Here we consider data-driven bandwidth selection based on the gradient of an unknown regression function. The procedure developed here is automatic and does not require initial estimation of unknown...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, `partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...

Modeling the cross-country distribution of per capita using mixture analysis provides a natural platform for the recovery or detection of clubs of countries. Unfortunately, these mixture methods, when based on a strictly univariate approach are limiting towards one's ability to learn about the...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...

Monte Carlo (MC) simulations are one of the dominant approaches to compare statistical methods. To date, there is no standard procedure for MC simulations. Although internally valid, they exhibit a certain degree of arbitrariness through the various choices that researchers make. In this paper,...

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...