| Library: | smoother |
| See also: | denest denci dencb denbwcrit denrot canker |
| Macro: | denbwsel | |
| Description: | interactive tool for bandwidth selection in univariate kernel density estimation. |
Haerdle (1991): Smoothing Techniques
Haerdle, Mueller, Sperlich, Werwatz (1999): Non- and Semiparametric Modelling
| Usage: | {hcrit,crit}= denbwsel(x {,h {,K} {,d} }) | |
| Input: | ||
| x | n x 1 vector, the data. | |
| h | m x 1 vector, vector of bandwidths. | |
| K | string, kernel function on [-1,1] or Gaussian kernel "gau". If not given, "gau" is used. | |
| d | scalar, discretization binwidth. d must be smaller than h. If not given, the minimum of min(h)/3 and (max(x)-min(x))/200 is used. | |
| Output: | ||
| hcrit | p x 1 vector, selected bandwidths by the different criteria. | |
| crit | p x 1 string vector, criteria considered for bandwidth selection. | |
library("smoother")
x=normal(500)
tmp=denbwsel(x)
You may interactively choose the bandwidth selector. The parameters (range of bandwidths, kernel K, binwidth d) can be changed as well.
| Library: | smoother |
| See also: | denest denci dencb denbwcrit denrot canker |