Nothing
LONRBGLSS <- function(y,e,X,g,w,z,k,quant,max.steps,sparse, structure){
n = nrow(g)
m = ncol(g)
p = ncol(w)
E = cbind(e,X)
o = ncol(X)
q = ncol(E)
c = ncol(z)
n1 = n/k
hatTau=1
hatV = rep(1,n)
hatSg1 = rep(1,m)
hatSg21= rep(1,p)
hatSg22 = rep(1,m)
xi1=(1-2*quant)/(quant*(1-quant))
xi2 = sqrt(2/(quant*(1-quant)))
hatEtaSq1=1
hatEtaSq2=1
r1=1
r2=1
a=1
b=1
hatAta=matrix(c(rep(1,n1*c)),nrow=c)
hatBeta = rep(1,m)
hatEta1 = rep(1,p)
hatEta2 = matrix(c(rep(1,p)),nrow=q-o)
hatAlpha = rep(1,q)
invSigAlpha0 = diag(rep(10^-3,q))
alpha1=1
gamma1=1
hatPhiSq=1
progress=0
hatPi1=1/2
hatPi2=1/2
sh1=1
sh0=1
debugging=FALSE
progress = ifelse(debugging, 10^(floor(log10(max.steps))-1), 0)
if(sparse){
fit=switch (structure,
"group" = RBGLSS(y,E,g,w,max.steps,q,o,k,hatBeta,hatEta2,hatAlpha,hatAta,z,hatTau,hatV,hatSg1,hatSg22,invSigAlpha0,
hatPi1,hatPi2,hatEtaSq1,hatEtaSq2,xi1,xi2,r1,r2,hatPhiSq,a,b,alpha1,gamma1,sh1,sh0,progress),
"individual" = RBLSS(y,E,g,w,max.steps,q,k,hatBeta,hatEta1,hatAlpha,hatAta,z,hatTau,hatV,hatSg1,hatSg21,invSigAlpha0,
hatPi1,hatPi2,hatEtaSq1,hatEtaSq2,xi1,xi2,r1,r2,hatPhiSq,a,b,alpha1,gamma1,sh1,sh0,progress)
)
}else{
fit=switch (structure,
"group" = RBGL(y,E,g,w,max.steps,q,o,k,hatBeta,hatEta2,hatAlpha,hatAta,z,hatTau,hatV,hatSg1,hatSg22,invSigAlpha0,
hatEtaSq1,hatEtaSq2,xi1,xi2,r1,r2,hatPhiSq,a,b,alpha1,gamma1,progress),
"individual" = RBL(y,E,g,w,max.steps,q,k,hatBeta,hatEta1,hatAlpha,hatAta,z,hatTau,hatV,hatSg1,hatSg21,invSigAlpha0,
hatEtaSq1,hatEtaSq2,xi1,xi2,r1,r2,hatPhiSq,a,b,alpha1,gamma1,progress)
)
}
out = list( GS.beta = fit$GS.beta,
GS.eta = fit$GS.eta)
out
}
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