rkpk {gss} | R Documentation |
Call RKPACK routines for numerical calculations for fitting and predicting from Smoothing Spline ANOVA models.
sspreg(s, q, y, method="v", varht=1) mspreg(s, q, y, method="v", varht=1, prec=1e-7, maxiter=30) sspregpoi(family, s, q, y, wt, offset, method="u", varht=1, alpha, prec=1e-7, maxiter=30) mspregpoi(family, s, q, y, wt, offset, method="u", varht=1, alpha, prec=1e-7, maxiter=30) getcrdr(obj, r) getsms(obj)
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 . |
alpha |
Optional argument for nbinomial, weibull, lognorm, and loglogis families. |
r |
Inputs for standard error calculation. |
sspreg
is used by ssanova
to fit Gaussian
models with a single smoothing parameter. mspreg
is used to
fit Gaussian models with multiple single smoothing parameters.
sspregpoi
is used by gssanova
to fit non
Gaussian models with a single smoothing parameter. mspregpoi
is used to fit non Gaussian models with multiple single smoothing
parameters.
getcrdr
and getsms
are used by
predict.ssanova
to calculate standard errors of the
fitted terms.
Gu, C. (1989), RKPACK and its applications: Fitting smoothing spline models. In ASA Proceedings of Statistical Computing Section, pp. 4251.