Usage: |
mh = lpregest (x, h {,p {,K} {,d}})
|
Input: |
| x | n x 2, the data. In the first column the
independent, in the second column the
dependent variable.
|
| h | scalar, bandwidth. If not given, the rule of thumb
bandwidth computed by lpregrot is used.
|
| p | integer, order of polynomial. If not given,
p=1 (local linear) is used. p=0 yields the
Nadaraya-Watson estimator.
|
| K | string, kernel function on [-1,1] or Gaussian
kernel "gau". If not given, the Quartic kernel
"qua" is used.
|
| d | scalar, discretization binwidth. d must be smaller
than h. If not given, the minimum of h/3 and
(max(x[,1])-min(x[,1]))/100 is used.
|
Output: |
| mh | m x 2 matrix, the first column is a grid and the
second column contains the regression estimate on
that grid. |