# predict.logit: Prediction for an object with S3 class '"logit"' In picasso: Pathwise Calibrated Sparse Shooting Algorithm

## Description

Predicting responses of the given design data.

## Usage

 1 2 ## S3 method for class 'logit' predict(object, newdata, lambda.idx = c(1:3), p.pred.idx = c(1:5), ...) 

## Arguments

 object An object with S3 class "logit" newdata An optional data frame in which to look for variables with which to predict. If omitted, the traning data of the are used. lambda.idx The indices of the regularizaiton parameters in the solution path to be displayed. The default values are c(1:3). p.pred.idx The indices of the predicted response vectors in the solution path to be displayed. The default values are c(1:5). ... Arguments to be passed to methods.

## Details

predict.logit produces predicted values of the responses of the newdata from the estimated beta values in the object, i.e.

\hat{p} = \frac{e^{\hat{β}_0 + X_{new} \hat{β}}}{1+e^{\hat{β}_0 + X_{new} \hat{β}}}.

## Value

 p.pred The predicted response vectors based on the estimated models.

## Author(s)

Jason Ge, Xingguo Li, Mengdi Wang, Tong Zhang, Han Liu and Tuo Zhao
Maintainer: Jason Ge <jiange@princeton.edu>

picasso and picasso-package.
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