extlasso.pois.lambda: Coefficients of penalized generalized linear models for a...

Description Usage Arguments Details Value Author(s)

View source: R/extlasso.R

Description

The function computes regression coefficients for a penalized generalized linear models for a given lambda value for response variable following Poisson distribution.

Usage

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extlasso.pois.lambda(n,p,p1,sumy,beta0.old,beta1.old,x,y,dxkx0,dxkx1, 
tau,lambda1,alpha,tol,maxiter,eps,xbeta.old,mu1)

Arguments

n

Number of observations

p

Number of predictors

p1

Number of active predictors

sumy

Sum of y values

beta0.old

Initial value of intercept

beta1.old

A vector of initial values of slope coefficients

x

A n by p1 matrix of predictors

y

A vector of n observations

dxkx0

In case of a model with intercept, first diagonal of X'X

dxkx1

Diagonals of X'X

tau

Elastic net paramter. Default is 1

lambda1

The value of lambda

alpha

Approximation to be used for absolute value. Default is 10^-6

tol

Tolerance criterion. Default is 10^-6

maxiter

Maximum number of iterations. Default is 10000

eps

value for which beta is set to zero if -eps<beta<eps. Default is 10^-6

xbeta.old

A n by 1 vector of xbeta values

mu1

The value of mu at beta.old

Details

This function is internal and used by extlasso.poisson function. User need not call this function.

Value

A list with following components

beta0.new

Intercept estimate

beta1.new

Slope coefficient estimates

conv

"yes" means converged and "no" means did not converge

iter

Number of iterations to estimate the coefficients

ofv.new

Objective function value at solution

xbeta.new

xbeta values at solution

mu1

Value of mu at solution

Author(s)

B N Mandal and Jun Ma


extlasso documentation built on May 2, 2019, 11:39 a.m.