predict.rgam: Make predictions from a "rgam" object
In relgam: Reluctant Generalized Additive Models

Description Usage Arguments Value See Also Examples

This function returns the predictions from a "rgam" object for a new data matrix.

1 2	## S3 method for class 'rgam' predict(object, xnew, ...)

`object`	Fitted "`rgam`" object.
`xnew`	Matrix of new values for `x` at which predictions are to be made.
`...`	Any other arguments to be passed to `predict.glmnet()`.

Predictions of which the model object makes at xnew. The type of predictions depends on whether a type argument is passed. By default it givs the linear predictors for the regression model.

If an offset is used in the fit, then one must be supplied via the newoffset option.

rgam.

set.seed(1)
n <- 100; p <- 20
x <- matrix(rnorm(n * p), n, p)
beta <- matrix(c(rep(2, 5), rep(0, 15)), ncol = 1)
y <- x %*% beta + rnorm(n)
fit <- rgam(x, y)

# predict for full lambda path
predict(fit, xnew = x[1:5, ])

# predict for specific lambda values
predict(fit, xnew = x[1:5, ], s = 0.1)

# predictions for binomial family
bin_y <- ifelse(y > 0, 1, 0)
fit2 <- rgam(x, bin_y, family = "binomial")
# linear predictors
predict(fit2, xnew = x[1:5, ], s = 0.05)
# probabilities
predict(fit2, xnew = x[1:5, ], type = "response", s = 0.05)