methods: Methods for class "palasso"

In palasso: Sparse Regression with Paired Covariates

Methods for class "palasso"

Description

This page lists the main methods for class "palasso".

Usage

## S3 method for class 'palasso'
predict(object, newdata, model = "paired", s = "lambda.min", max = NULL, ...)

## S3 method for class 'palasso'
coef(object, model = "paired", s = "lambda.min", max = NULL, ...)

## S3 method for class 'palasso'
weights(object, model = "paired", max = NULL, ...)

## S3 method for class 'palasso'
fitted(object, model = "paired", s = "lambda.min", max = NULL, ...)

## S3 method for class 'palasso'
residuals(object, model = "paired", s = "lambda.min", max = NULL, ...)

## S3 method for class 'palasso'
deviance(object, model = "paired", max = NULL, ...)

## S3 method for class 'palasso'
logLik(object, model = "paired", max = NULL, ...)

## S3 method for class 'palasso'
summary(object, model = "paired", ...)

Arguments

object	palasso object
newdata	covariates: list of matrices, each with n rows (samples) and p columns (variables)
model	character "paired", or an entry of names(object)
s	penalty parameter: character "lambda.min" or "lambda.1se", positive numeric, or NULL (entire sequence)
max	maximum number of non-zero coefficients, positive integer, or NULL
...	further arguments for predict.cv.glmnet, coef.cv.glmnet, or deviance.glmnet

Details

By default, the function predict returns the linear predictor (type="link"). Consider predicting the response (type="response").

See Also

Use palasso to fit the paired lasso.

palasso documentation built on Sept. 30, 2024, 9:30 a.m.