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

 Quantlet: lpderxest Description: estimates the q-th derivative of a regression function using local polynomial kernel regression with Quartic kernel.

Reference(s):
Fan and Gijbels (1995): Local Polynomial Fitting Fan and Marron (1994): Binning for local polynomials Haerdle (1991): Smoothing Techniques

 Usage: mh = lpderxest (x, h {,q {,p {,K} {,v}}}) 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 lpderrot is used. q integer <=2, order of derivative. If not given, q=1 (first derivative) is used. p integer, order of polynomial. If not given, p=q+1 is used for q<2, p=q is used for q=2. v m x 1, values of the independent variable on which to compute the regression. If not given, x is used. Output: mh n x 2 or m x 2 matrix, the first column is the sorted first column of x or the sorted v, the second column contains the derivative estimate on the values of the first column.

Example:
```library("smoother")
library("plot")
;
mh = lpderxest(x,5)      ; estimate function
;
```The derivative regession estimate (blue) using