print.gfmR: print method for group fused multinomial logistic regression

Description Usage Arguments Details Value Author(s) References Examples

Description

This routine fits the group fused multinomial logistic regression model, which uses fusion shrinkage to automatically combine response categories.

Usage

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## S3 method for class 'gfmR'
print(x,...)

Arguments

x

A gfmr object which specifically is the output from the GroupFusedMulti function.

...

Other arguments

Details

Prediction function for GFMR

Value

A vector or a matrix corresponding to type return.

Author(s)

Brad Price, brad.price@mail.wvu.edu.

References

Price, B.S, Geyer, C.J. and Rothman, A.J. "Automatic Response Category Combination in Multinomial Logistic Regression." https://arxiv.org/abs/1705.03594.

Examples

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## Not run: data(nes96)
attach(nes96)
Response=matrix(0,944,7)
for(i in 1:944){
  if(PID[i]=="strRep"){Response[i,1]=1}
  if(PID[i]=="weakRep"){Response[i,2]=1}
  if(PID[i]=="indRep"){Response[i,3]=1}
  if(PID[i]=="indind"){Response[i,4]=1}
  if(PID[i]=="indDem"){Response[i,5]=1}
  if(PID[i]=="weakDem"){Response[i,6]=1}
  if(PID[i]=="strDem"){Response[i,7]=1}
}

Hmat=matrix(1,dim(Response)[2],dim(Response)[2])
diag(Hmat)=0
ModMat<-lm(popul~age,x=TRUE)$x

X=cbind(ModMat[,1],apply(ModMat[,-1],2,scale))
mod<-GroupFusedMulti(Response,X,lambda=2^4.3,H=Hmat2,rho=10^2,iter=50,tol1=10^-4,tol2=10^-4)
mod

## End(Not run)

gfmR documentation built on May 1, 2019, 8:41 p.m.