Dear fellow R users, I just uploaded a new package gss to ftp.ci.tuwien.ac.at. The package name gss stands for General Smoothing Spline. In the current version (0.4-1), it handles nonparametric multivariate regression with Gaussian, Binomial, Poisson, Gamma, Inverse Gaussian, and Negative Binomial responses. I am still working on code for density estimation and hazard rate estimation to be made available in future releases. On the modeling side, gss uses tensor-product smoothing splines to construct nonparametric ANOVA structures using cubic spline, linear spline, and thin-plate spline marginals. The popular (main-effect-only) additive models are special cases of nonparametric ANOVA models. The syntax of gss functions resembles that of the lm and glm suites. Among new features that are not available from other spline packages are the standard errors needed for the construction of Wahba's Bayesian confidence intervals for smoothing spline fits, so you may want to try out gss even if you only wants to calculate a univariate cubic spline or a single term thin-plate spline. For those familiar with smoothing splines, gss is a front end to RKPACK, which encodes O(n^3) generic algorithms for reproducing kernel based smoothing spline calculation. Reports on bugs and suggestions for improvements/new features are most welcome. Chong Gu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-announce mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-announce-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._