| predict.ssanova(gss) | R Documentation |
predict.ssanova evaluates a smoothing spline ANOVA fit at
arbitrary data points as specified in newdata. The model
terms to be included in the evaluation are specified via
include, which defaults to all terms in the model.
With the flag se.fit=TRUE, the standard errors of the fit are
also calculated, which are to be used to construct Bayesian
confidence intervals of the fit.
predict[.ssanova](obj, newdata, se.fit=FALSE, include=obj$terms$labels)
obj |
an object of class "ssanova". |
newdata |
a data frame or model frame. |
se.fit |
a logical flag. |
include |
a list of model terms to be included in the
prediction. The partial and offset terms, if
present, are specified by "partial" and "offset",
respectively. |
se.fit=FALSE, predict.ssanova returns a vector of
the evaluated fit.
For se.fit=TRUE, predict.ssanova returns a list
consisting of the following components.
fit |
a vector of the evaluated fit. |
se.fit |
a vector of the corresponding standard errors. |
Chong Gu, chong@stat.purdue.edu
The model fitting function ssanova and the summarizing
function summary.ssanova.
## Fit a model with thin-plate marginals, where geog is 2-D
data(lake.acid)
fit <- ssanova(ph~log(cal)*geog,"tp",lake.acid)
## Obtain estimates and standard errors on a grid
new <- data.frame(cal=1,geog=I(matrix(0,1,2)))
new <- model.frame(~log(cal)+geog,new)
predict(fit,new,se=TRUE)
## Evaluate the geog main effect
predict(fit,new,se=TRUE,inc="geog")
## Evaluate the sum of the geog main effect and the interaction
predict(fit,new,se=TRUE,inc=c("geog","log(cal):geog"))
## Evaluate the geog main effect on a grid
grid <- seq(-.04,.04,len=21)
new <- model.frame(~geog,list(geog=cbind(rep(grid,21),rep(grid,rep(21,21)))))
est <- predict(fit,new,se=TRUE,inc="geog")
## Plot the fit and standard error
par(pty="s")
contour(grid,grid,matrix(est$fit,21,21),col=1)
contour(grid,grid,matrix(est$se,21,21),add=TRUE,col=2)