Fit a GAMM or GAMM4 model and get a gamViz object
These are wrappers that fit GAM models using mgcv::gamm or gamm4::gamm4 and
convert them to a gamViz object using the getViz function.
It is essentially a shortcut.
gamm4V( formula, random, family = gaussian(), data = list(), REML = TRUE, aGam = list(), aViz = list(), keepGAMObj = FALSE ) gammV( formula, random, family = gaussian(), data = list(), method = "REML", aGam = list(), aViz = list(), keepGAMObj = FALSE )
formula, random, family, data |
same arguments as in mgcv::gamm or gamm4::gamm4. |
REML |
same as in gamm4::gamm4 |
aGam |
list of further arguments to be passed to mgcv::gamm or gamm4::gamm4. |
aViz |
list of arguments to be passed to getViz. |
keepGAMObj |
if |
method |
same as in mgcv::gamm |
WARNING: Model comparisons (e.g. with anova) should only be done using the mixed model part as described in gamm4::gamm4.
For mgcv::gamm please refer to the original help file.
An object of class "gamViz" which can, for instance, be plotted using plot.gamViz. Also the object has the following additional elements:
lme mixed model as in mgcv::gamm
mer mixed model as in gamm4::gamm4
gam a copy of the gamViz Object if setting keepGAMObj = TRUE.
##### gam example library(mgcViz) # Simulate data dat <- gamSim(1,n=400,scale=2) ## simulate 4 term additive truth ## Now add 20 level random effect `fac'... dat$fac <- fac <- as.factor(sample(1:20,400,replace=TRUE)) dat$y <- dat$y + model.matrix(~fac-1) %*% rnorm(20) * 0.5 br <- gammV(y~s(x0)+x1+s(x2), data=dat,random=list(fac=~1)) summary(br) plot(br) summary(br$lme) ## Not run: ## gamm4::gamm4 example br4 <- gamm4V(y~s(x0)+x1+s(x2),data=dat,random=~(1|fac)) summary(br4) plot(br4) summary(br4$mer) ## End(Not run)
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