similar to: npindex: fitted values of the function itself?

Dear R-users, I am very enthusiastic about the capacities offered by the np package and pretty fond of it. Nevertheless, trying to estimate Ichimura and Klein and Spady models on my data, I would like to be able to provide the npindex function with my guesses for the bandwidth (eventually computed by other means). The fact that the option 'bandwidth.compute' in the function npindexbw

Full_Name: Maxime To Version: 2.9 OS: WIndows Submission from: (NULL) (81.57.236.122) I am using the npindex and npindexbw fubctions of the NP package. I would like to compute the predicted values of the model and tried to use the predict function for this purpose but the function only gives me the summary of the model but no vector of predicted values as with any other model. Simply using the

Dear all, I am using np package in order to estimate a model with Klein and Spady estimator. To estimate the model I use KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady", optim.maxit=10^3, ckertype="epanechnikov", ckerorder=2) and to estimate beta hats standard errors I use KSi <- npindex(KS, gradients=T, boot.num=300) vcov(KSi) This is

Dear R-Help, I am Deniz. I am currently trying to replicate a semiparametric sample selection paper and I am working on Klein and Spady estimator. I am using the npindex() and npindexbw() functions. The problem is, I need results for single bandwidth and when I set bandwidth computation to "FALSE" mode, R is not optimizing anything. Here is the code I am using:

Dear all, I would like to estimate the standard errors of Klein and Spady's estimator for that I am using: library(np) N<-100 X<-matrix(c(rnorm(N,1,1), rnorm(N,0,1)), ncol=2) BETA <-matrix(1,2,1) Z<-X%*%BETA L<-rlogis(N,location=0, scale=1) Y <-as.vector(X%*%BETA+L>=0)*1 KS <- npindexbw (xdat=X, ydat=Y, bandwidth.compute=TRUE, method="kleinspady",