rkpk0: Interface to RKPACK

Description

Call RKPACK routines for numerical calculations concerning the ssanova0 and gssanova0 suites.

Usage

sspreg0(s, q, y, method="v", varht=1)
mspreg0(s, q, y, method="v", varht=1, prec=1e-7, maxiter=30)
sspregpoi(family, s, q, y, wt, offset, method="u", varht=1, nu, prec=1e-7, maxiter=30)
mspregpoi(family, s, q, y, wt, offset, method="u", varht=1, nu, prec=1e-7, maxiter=30)
getcrdr(obj, r)
getsms(obj)

Arguments

s: Design matrix of unpenalized terms.
q: Penalty matrices of penalized terms.
y: Model response.
method: Method for smoothing parameter selection.
varht: Assumed dispersion parameter, needed only for method="u".
prec: Precision requirement for iterations.
maxiter: Maximum number of iterations allowed.
family: Error family.
wt: Model weights.
offset: Model offset.
obj: Object returned from a call to sspreg, mspreg, sspregpoi, or mspregpoi.
nu: Optional argument for nbinomial, weibull, lognorm, and loglogis families.
r: Inputs for standard error calculation.

Details

sspreg0 is used by ssanova0 to fit Gaussian models with a single smoothing parameter. mspreg0 is used to fit Gaussian models with multiple smoothing parameters.

sspregpoi is used by gssanova0 to fit non Gaussian models with a single smoothing parameter. mspregpoi is used to fit non Gaussian models with multiple smoothing parameters.

getcrdr and getsms are used by predict.ssanova0 to calculate standard errors of the fitted terms.

References

Gu, C. (1989), RKPACK and its applications: Fitting smoothing spline models. In ASA Proceedings of Statistical Computing Section, pp. 42--51.

Gu, C. (1992), Cross validating non Gaussian data. Journal of Computational and Graphical Statistics, 1, 169--179.