gamm4V | R Documentation |
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 = NULL,
family = gaussian(),
data = list(),
REML = TRUE,
aGam = list(),
aViz = list(),
keepGAMObj = FALSE
)
gammV(
formula,
random = NULL,
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.