We analyze the performance of kernel density methods applied to grouped data to estimate poverty (as applied in Sala-i-Martin, 2006, QJE). Using Monte Carlo simulations and household surveys, we find ...

Nonparametric techniques, such as kernel density estimation and wavelet methods, have become standard tools due to their flexibility in capturing complex data structures.

Kernel Density Estimation and Nonparametric Methods Publication Trend The graph below shows the total number of publications each year in Kernel Density Estimation and Nonparametric Methods.

We consider kernel estimation of a univariate density whose support is a compact interval. If the density is non-zero at either boundary, then the usual kernel estimator can be seriously biased.

We consider kernel-type methods for the estimation of a density on [0, 1] which eschew explicit boundary correction. We propose using kernels that are symmetric in their two arguments; these kernels ...