rkpk0 | R Documentation |
Call RKPACK routines for numerical calculations concerning the
ssanova0
and gssanova0
suites.
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)
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
|
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 |
nu |
Optional argument for nbinomial, weibull, lognorm, and loglogis families. |
r |
Inputs for standard error calculation. |
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.
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.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.