New smoothing spline package gss

[Chong Gu]

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 
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