He folks, I want to use quantile regression for doing a test of symmetrie of a distribution. Following Buchinsky I want to test, whether the square of \tau = \beta(p)+\beta(1-p)-2*\beta(0.5) (\beta(\tau) is the estimated slope parameter for quantile \tau).Unfortunately I do not know how to implement design bootstrap matrix for calculating the standard error. Do you know if there is an existent package computing the necessesary statistics for me? Or do you have an idea how to calculate the standard error? I know that this question contains several big issues and I am very sorry that it is not possible for me to do it for my self or at least to present some parts of it...thank you very, very much for every comment!
Cheers Stefan -- View this message in context: http://r.789695.n4.nabble.com/R-quantreg-symmetry-test-bootstrap-SE-tp4631662.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.