Description Usage Arguments Author(s) References See Also Examples
This function makes predictions at particular points along the fitted
glmpath.
The linear predictor, estimated response,
log-likelihood, or the coefficients can be computed.
1 2 3 4 5 6 |
object |
a |
newx |
a matrix of features at which the predictions are made. If
|
newy |
a vector of responses corresponding to |
s |
the values of |
type |
If |
mode |
what |
weight |
an optional vector of weights for observations. |
offset |
If |
eps |
an effective zero |
... |
other options for the prediction |
Mee Young Park and Trevor Hastie
Mee Young Park and Trevor Hastie (2007) L1 regularization path algorithm for generalized linear models. J. R. Statist. Soc. B, 69, 659-677.
cv.glmpath, glmpath, plot.glmpath
1 2 3 4 5 | data(heart.data)
attach(heart.data)
fit <- glmpath(x, y, family=binomial)
pred <- predict(fit, x, s = seq(0, 1, length=10), mode="norm.fraction")
detach(heart.data)
|
Loading required package: survival
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