Optimal CV BW estimation for strictly positive distributions.

Computes least squares cross-validation (CV) bandwidth (BW) for log domain KDE.

Usage

bw.logCV(x, grid = 21, NB = 512)

x: numeric vector of the data. Must be strictly positive, will be log transformed during estimation.
grid: number of points used for BW selection CV grid.
NB: number of points at which to estimate the KDE at during the CV loop.

bw the optimal least squares CV bandwidth.

Silverman, B. W. (1986). Density estimation for statistics and data analysis. Monographs on Statistics and Applied Probability. 26.

Stone, C. J. (1984). An asymptotically optimal window selection rule for kernel density estimates. The Annals of Statistics, 12(4), 1285-1297.

bw.logCV(rchisq(100,10), grid=21, NB=512)
#> [1] 0.2684358