Nothing
imperfect.CopulaREMADA.loglik.norm<-function(param,y11,y10,y01,y00,gl,mgrid,qcond,
tau2par,select.random)
{ p=param[1:5]
si=param[6:7]
tau=param[8]
if(tau< -0.95 | tau>0.95) return(1.e10)
p=expit(p)
if(p[3]+p[5]-1<0) return(1e10)
si=exp(si)
u1=mgrid$x
th=tau2par(tau)
u2=qcond(mgrid$y,mgrid$x,th)
mu=log(p[select.random]/(1-p[select.random]))
x1=qnorm(u1,mu[1],si[1])
x2=qnorm(u2,mu[2],si[2])
t1=exp(x1)
t2=exp(x2)
x1=t1/(1+t1)
x2=t2/(1+t2)
x = array(NA, dim = c(2,dim(x1)))
x[1,,]=x1
x[2,,]=x2
lst=list(x1=1,x2=1,x3=1,x4=1,x5=1)
for(jj in 1:length(select.random)) lst[[select.random[jj]]]=x[jj,,]
for(ii in (1:5)[-select.random]) lst[[ii]]=p[ii]
N=length(y11)
prob=rep(NA,N)
for(i in 1:N)
#out=foreach(i=1:N,.combine='+') %dopar%
{ temp=imperfect.multinomprod(lst,y11[i],y10[i],y01[i],y00[i])
prob[i]= prob[i]=gl$w %*% temp %*% as.matrix(gl$w)
#if(prob!=0) -log(prob) else 0
}
-sum(log(prob[prob!=0]))
}
imperfectCopulaREMADA.norm=function(y11,y10,y01,y00,
gl,mgrid,qcond,tau2par,select.random,start)
{ start=c(logit(start[1:5]),log(start[6:7]),start[8])
est=nlm(imperfect.CopulaREMADA.loglik.norm,start,y11,y10,y01,y00,
gl,mgrid,qcond,tau2par,select.random,
hessian=T,print.level =2,iterlim=1000)
se=sqrt(diag(solve(est$hessian)))
list(LogLikelihood=-est$m,Estimates=c(expit(est$e[1:5]),exp(est$e[6:7]),est$e[8]),
SE=c(se.p(est$e[1:5],se[1:5]),se.si(est$e[6:7],se[6:7]),se[8]))
}
imperfect.CopulaREMADA.loglik.beta<-function(param,y11,y10,y01,y00,gl,mgrid,qcond,
tau2par,select.random)
{ p=param[1:5]
g=param[6:7]
tau=param[8]
if(tau< -0.95 | tau>0) return(1.e10)
p=expit(p)
g=expit(g)
u1=mgrid$x
th=tau2par(tau)
u2=qcond(mgrid$y,mgrid$x,th)
a=p[select.random]/g-p[select.random]
b=(1-p[select.random])*(1-g)/g
x1=qbeta(u1,a[1],b[1])
x2=qbeta(u2,a[2],b[2])
x = array(NA, dim = c(2,dim(x1)))
x[1,,]=x1
x[2,,]=x2
lst=list(x1=1,x2=1,x3=1,x4=1,x5=1)
for(jj in 1:length(select.random)) lst[[select.random[jj]]]=x[jj,,]
for(ii in (1:5)[-select.random]) lst[[ii]]=p[ii]
N=length(y11)
prob=rep(NA,N)
for(i in 1:N)
#out=foreach(i=1:N,.combine='+') %dopar%
{ temp=imperfect.multinomprod(lst,y11[i],y10[i],y01[i],y00[i])
prob[i]= prob[i]=gl$w %*% temp %*% as.matrix(gl$w)
#if(prob!=0) -log(prob) else 0
}
-sum(log(prob[prob!=0]))
#out
}
imperfectCopulaREMADA.beta=function(y11,y10,y01,y00,gl,mgrid,qcond,
tau2par,select.random,start)
{ start=c(logit(start[1:5]),logit(start[6:7]),start[8])
est=nlm(imperfect.CopulaREMADA.loglik.beta,start,y11,y10,y01,y00,
gl,mgrid,qcond,tau2par,select.random,
hessian=T,print.level =2,iterlim=1000)
se=sqrt(diag(solve(est$hessian)))
list(LogLikelihood=-est$m,Estimates=c(expit(est$e[1:5]),expit(est$e[6:7]),est$e[8]),
SE=c(se.p(est$e[1:5],se[1:5]),se.p(est$e[6:7],se[6:7]),se[8]))
}
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