Usage
predict.glmpath(object, newx, newy, s, type = c("link", "response", "loglik", "coefficients"), mode = c("step", "norm.fraction", "norm", "lambda.fraction", "lambda"), weight = NULL, offset = NULL, eps = .Machine$double.eps, ...)
Arguments
newx
a matrix of features at which the predictions are made. If
type=link, type=response, or type=loglik,
newx is required.
newy
a vector of responses corresponding to newx. If
type=loglik, newy is required.
s
the values of mode at which the predictions are made
type
If type=link, the linear predictors are returned; if
type=response, the estimated responses are returned; if
type=loglik, the log-likelihoods are returned, and if
type=coefficients, the coefficients are returned. The
coefficients for the initial input variables are returned (rather
than the standardized coefficients). Default is link.
mode
what mode=s refers to. If mode=step, s is the
number of steps taken; if mode=norm.fraction, s is the
fraction of the L1 norm of the standardized coefficients (with
respect to the largest norm); if mode=norm, s is the
L1 norm of the standardized coefficients; if
mode=lambda.fraction, s is the fraction of
log($\lambda$); and if mode=lambda, s is
$\lambda$. Default is step.
weight
an optional vector of weights for observations. weight is
effective only if type=loglik.
...
other options for the prediction