getF {cplm} | R Documentation |
Get and plot the estimated smoothing function values
getF(object, which, n=100, newdata, interval=c("NONE", "MCMC", "RW"), addConst=TRUE, varying=1, level=0.9, sims=1000) plotF(object, which, n=100, interval="RW", addConst=TRUE, trans=I, level=0.9, sims=1000, auto.layout=TRUE, rug=TRUE, legendPos="topright", ...)
object |
a fitted |
which |
(optional) an integer vector or a character vector of names giving the smooths for which fitted values are desired. Defaults to all. |
n |
if no |
newdata |
An optional data frame in which to look for variables with which to predict |
interval |
what mehod should be used to compute pointwise confidence/HPD intervals: RW= bias-adjusted empirical bayes |
addConst |
boolean should the global intercept and intercepts for the levels of the by-variable be included in the fitted values (and their CIs) can also be a vector of the same length as |
varying |
value of the |
level |
level for the confidence/HPD intervals |
sims |
how many iterates should be generated for the MCMC-based HPD-intervals |
trans |
a function that should be applied to the fitted values and ci's before plotting (e.g. the inverse link function to get plots on the scale of the reponse) |
auto.layout |
automagically set plot layout via |
rug |
add |
legendPos |
a (vector of) keyword(s) where to put labels of by-variables (see |
... |
arguments passed on to the low-level plot functions ( |
a list with one data.frame
for each function, giving newdata
or the values of the generated grid plus the fitted values (and confidence/HPD intervals).
These are from the amer
package that has retired from CRAN. The formula used for the pointwise bias-adjusted CIs is taken from Ruppert and Wand's 'Semiparametric Regression' (2003), p. 140.
These leave out the uncertainty associated with the variance component estimates.
Fabian Scheipl fabian.scheipl@googlemail.com
See the vignette for examples