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Last data update: 2014.03.03

R: Compute coefficients

coef.LarsPath

R Documentation

Compute coefficients

Description

Compute coefficients at a given level of penalty

Usage

## S3 method for class 'LarsPath'
coef(object, index = NULL, mode = c("lambda", "step",
  "fraction", "norm"), ...)

Arguments

`object`	a LarsParth object
`index`	If mode ="norm", index represents the l1-norm of the coefficients with which we want to predict. If mode="fraction", index represents the ratio (l1-norm of the coefficientswith which we want to predict)/(l1-norm maximal of the LarsPath object). If mode="lambda", index represents the value of the penalty parameter. If mode="step", index represents the numer of the step at which we want coefficients.
`mode`	"fraction" or "norm" or "lambda" or "step".
`...`	other arguments. Not used

Value

A vector containing the estimated coefficient for index

Author(s)

Quentin Grimonprez

Examples

dataset=simul(50,10000,0.4,10,50,matrix(c(0.1,0.8,0.02,0.02),nrow=2))
result=HDlars(dataset$data[1:40,],dataset$response[1:40])
coeff=coef(result,0.3,"fraction")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(HDPenReg)
Loading required package: rtkore
Loading required package: Rcpp

Attaching package: 'rtkore'

The following object is masked from 'package:Rcpp':

    LdFlags

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HDPenReg/coef.LarsPath.Rd_%03d_medium.png", width=480, height=480)
> ### Name: coef.LarsPath
> ### Title: Compute coefficients
> ### Aliases: coef.LarsPath
> 
> ### ** Examples
> 
> dataset=simul(50,10000,0.4,10,50,matrix(c(0.1,0.8,0.02,0.02),nrow=2))
> result=HDlars(dataset$data[1:40,],dataset$response[1:40])
> coeff=coef(result,0.3,"fraction")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>