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 Quantlet: regxci Description: computes pointwise confidence intervals with a pre-specified confidence level for univariate regression using the Nadaraya-Watson estimator.

Reference(s):
Haerdle, W. (1990). Applied Nonparametric Regression. Econometric Society Monographs, No. 19. Cambridge University Press. Haerdle, W. (1991). Smoothing Techniques. With Implementations in S. Springer, New York, p. 220.

 Usage: {mh, clo, cup} = regxci(x {,h {,alpha {,K} {,v} }}) Input: x n x 2 matrix, the data. The first column contains the independent variable and the second column the dependent variable. h optional scalar, bandwidth. If not given, 20% of the range of x[,1] is used as default. alpha optional scalar, confidence level; default alpha = 0.05. K optional string, kernel function on [-1,1]; default = "qua". v optional m x 1 vector, values of the independent variable in which to compute the regression and the confidence intervals. If not given, the (sorted) x is used. Output: mh n x 2 or m x 2 matrix, the first column represents the sorted first column of x or the sorted v and the second column contains the regression estimate on the values of the first column. clo n x 2 or m x 2 matrix, the first column represents the sorted first column of x or the sorted v and the second column contains the lower confidence bounds on the values of the first column. cup n x 2 or m x 2 matrix, the first column contains the sorted first column of x or the sorted v and the second one the upper confidence bounds on the values of the first column.

Note:
This function does an exact computation, i.e., requires O(n^2) operations for estimating the regression function on all observations. For exploratory purposes, the quantlet "regci" is recommended, which uses the faster WARPing method.

Example:
```library("smoother")
library("plot")
{mh, clo, cup} = regxci(x,3)
;
```Pointwise confidence intervals at confidence level