Library: | metrics |
See also: | adeind adeslp |
Quantlet: | dwade | |
Description: | dwade estimation of the density weighted average derivatives |
Usage: | d = dwade(x,y,h) | |
Input: | ||
x | n x d matrix , the observed explanatory variable | |
y | n x 1 matrix , the observed response variable | |
h | d x 1 or 1 x 1 matrix , chosen bandwidth | |
Output: | ||
d | d x 1 matrix, the density weighted average derivative estimator |
library("metrics") randomize(0) n = 100 x = normal(n,3) z = 0.2*x[,1] - 0.7*x[,2] + x[,3] eps = normal(n,1) * sqrt(0.5) y = 2 * z^3 + eps h = 0.3 d = dwade(x,y,h) d
the density weighted average derivative estimator of Powell, Stock and Stoker, Econometrica (1989)