library("gamlss2")
air <- subset(airquality, !is.na(Ozone))
air$Tc <- cut(air$Temp, breaks = seq(50, 100, by = 10),
include.lowest = TRUE)
air$Wc <- cut(air$Wind, breaks = seq(2, 22, by = 4),
include.lowest = TRUE)
## model formula, for each parameter we use
## the same gnet() model term
f <- Ozone ~ gnet(~Tc + Wc) | .
## estimate model
m <- gamlss2(f, data = air, family = NO)
## summary with edf
summary(m)
## plot coefficient paths
sp <- specials(m, model = "mu", term = "gnet(", element = "model")
print(class(sp))
plot(sp)Model Terms with glmnet
Description
Constructor for estimating penalized model terms using the glmnet package.
Usage
gnet(formula, ...)
Arguments
formula
|
A formula specifying the covariates that should be estimated using the glmnet implementation. |
…
|
Control arguments passed to glmnet and the information-criterion-based shrinkage selection.
|
Details
gnet() constructs a model.matrix representation of the supplied formula and delegates estimation to glmnet inside the backfitting algorithm. The optimal penalty parameter is selected using an information criterion, with criterion = “bic” used by default.
Value
A special model-term object used internally by gamlss2.
See Also
la, gamlss2, specials.