Dear list, I am using the np package. With the npindex function I estimate a semiparametric single index model using the method of Klein-Spady. P(Z=1|X) = G(X?b) I don?t have any problems to calculated the fitted values and standard errors X?b: bw = npindexbw(xdat=x, ydat=y_bi, method="kleinspady", nmulti=2) model = npindex(bws= bw3, gradients= TRUE, residuals = TRUE, boot.num = 50) x_fit = predict(model, se.fit = TRUE) x_fit_bi= x_fit$fit x_fit_bi_se = x_fit$se.fit However, I also would like to obtain an estimate of G(X?b). For example, after estimating a probit model, it would simply be G_hat=pnorm(x_fit) Any help would be very much appreciated! -- View this message in context: http://r.789695.n4.nabble.com/npindex-fitted-values-of-the-function-itself-tp4637070.html Sent from the R help mailing list archive at Nabble.com.
npindex: fitted values of the function itself?
2 messages · Kristin
3 days later
Dear list, I realized my mistake! For those who are interested: what I predicted was in fact G*(X'b*): A single-index model assumes a linear index function for which I obtain the estimated coefficients b*. The predicted probabilities are then G*(X'b*). Indeed, this is equivalent to the probit case, where I only need "G_hat=pnorm(x_fit) " if x_fit is the linear prediction. Best, Kristin -- View this message in context: http://r.789695.n4.nabble.com/npindex-fitted-values-of-the-function-itself-tp4637070p4637408.html Sent from the R help mailing list archive at Nabble.com.