Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: smoother
See also: denest denci dencb denbwcrit denrot canker

Quantlet: denbwsel
Description: interactive tool for bandwidth selection in univariate kernel density estimation.

Reference(s):

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.

Note:

Example:

library("smoother")

x=normal(500)

tmp=denbwsel(x)

Result:

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

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Marco Bianchi & Sigbert Klinke, 930722 Lijian Yang, 961026; Marlene Mueller, 990413
(C) MD*TECH Method and Data Technologies, 21.9.2000