R/bcontROB.R
In KironmoyDas/KD-STAT0035-GMupdate: Generalised Joint Regression Modelling
Defines functions
bcontROB
Documented in
bcontROB
bcontROB <- function(params, respvec, VC, ps, AT = FALSE){
p1 <- p2 <- pdf1 <- pdf2 <- c.copula.be2 <- c.copula.be1 <- c.copula2.be1be2 <- NA
eta1 <- VC$X1%*%params[1:VC$X1.d2]
eta2 <- VC$X2%*%params[(VC$X1.d2 + 1):(VC$X1.d2 + VC$X2.d2)]
etad <- etas1 <- etas2 <- l.ln <- NULL
if(is.null(VC$X3)){
sigma21.st <- etas1 <- params[(VC$X1.d2 + VC$X2.d2 + 1)]
sigma22.st <- etas2 <- params[(VC$X1.d2 + VC$X2.d2 + 2)]
teta.st <- etad <- params[(VC$X1.d2 + VC$X2.d2 + 3)]
}
if(!is.null(VC$X3)){
sigma21.st <- etas1 <- VC$X3%*%params[(VC$X1.d2 + VC$X2.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2)]
sigma22.st <- etas2 <- VC$X4%*%params[(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2)]
teta.st <- etad <- VC$X5%*%params[(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2 + VC$X5.d2)]
}
##################
## Transformations
##################
sstr1 <- esp.tr(sigma21.st, VC$margins[1])
sstr2 <- esp.tr(sigma22.st, VC$margins[2])
sigma21.st <- sstr1$vrb.st
sigma22.st <- sstr2$vrb.st
sigma21 <- sstr1$vrb
sigma22 <- sstr2$vrb
eta1 <- eta.tr(eta1, VC$margins[1])
eta2 <- eta.tr(eta2, VC$margins[2])
resT <- teta.tr(VC, teta.st)
teta.st <- resT$teta.st
teta <- resT$teta
##################
##################
dHs1 <- distrHs(respvec$y1, eta1, sigma21, sigma21.st, nu = 1, nu.st = 1, margin2=VC$margins[1], naive = FALSE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
dHs2 <- distrHs(respvec$y2, eta2, sigma22, sigma22.st, nu = 1, nu.st = 1, margin2=VC$margins[2], naive = FALSE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
pdf1 <- dHs1$pdf2
pdf2 <- dHs2$pdf2
p1 <- dHs1$p2
p2 <- dHs2$p2
dH <- copgHsAT(p1, p2, teta, VC$BivD, Ln = TRUE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr, par2 = VC$dof)
c.copula2.be1be2 <- dH$c.copula2.be1be2
l.par1 <- log(pdf1) + log(pdf2) + log(c.copula2.be1be2)
Robj.lpar <- llpsi(l.par1, VC$tc)
psi <- Robj.lpar$psi
d.psi <- Robj.lpar$d.psi
d2.psi <- Robj.lpar$d2.psi
l.par <- VC$weights*( psi )
##################
##################
derpdf1.dereta1 <- dHs1$derpdf2.dereta2
derpdf1.dersigma21.st <- dHs1$derpdf2.dersigma2.st
derpdf2.dereta2 <- dHs2$derpdf2.dereta2
derpdf2.dersigma22.st <- dHs2$derpdf2.dersigma2.st
derp1.dereta1 <- dHs1$derp2.dereta2
derp1.dersigma21.st <- dHs1$derp2.dersigma.st
derp2.dereta2 <- dHs2$derp2.dereta2
derp2.dersigma22.st <- dHs2$derp2.dersigma.st
BITS <- copgHsCont(p1, p2, teta, teta.st, VC$BivD, Cont = TRUE, par2 = VC$dof, nu.st = log(VC$dof - 2))
der2h.derp1p1 <- BITS$der2h.derp1p1
derc.dereta1 <- der2h.derp1p1 * derp1.dereta1
derc.dersigma21.st <- der2h.derp1p1 * derp1.dersigma21.st
der2h.derp1p2 <- BITS$der2h.derp1p2
derc.dereta2 <- der2h.derp1p2 * derp2.dereta2
derc.dersigma22.st <- der2h.derp1p2 * derp2.dersigma22.st
der2h.derp1teta <- BITS$der2h.derp1teta
derteta.derteta.st <- BITS$derteta.derteta.st
der2h.derp1teta.st <- der2h.derp1teta * derteta.derteta.st # new bit
dl.dbe1.0 <- derpdf1.dereta1/pdf1 + derc.dereta1/c.copula2.be1be2
dl.dbe2.0 <- derpdf2.dereta2/pdf2 + derc.dereta2/c.copula2.be1be2
dl.dsigma21.st.0 <- derpdf1.dersigma21.st/pdf1 + derc.dersigma21.st/c.copula2.be1be2
dl.dsigma22.st.0 <- derpdf2.dersigma22.st/pdf2 + derc.dersigma22.st/c.copula2.be1be2
dl.dteta.st.0 <- der2h.derp1teta.st/c.copula2.be1be2
dl.dbe1 <- VC$weights*( d.psi*dl.dbe1.0 )
dl.dbe2 <- VC$weights*( d.psi*dl.dbe2.0 )
dl.dsigma21.st <- VC$weights*( d.psi*dl.dsigma21.st.0 )
dl.dsigma22.st <- VC$weights*( d.psi*dl.dsigma22.st.0 )
dl.dteta.st <- VC$weights*( d.psi*dl.dteta.st.0 )
#################################################################################################
der2c.derrho.derrho <- BITS$der2c.derrho.derrho
der2c.derp1.derp1 <- BITS$der2c.derp1.derp1
der2c.derp2.derp2 <- BITS$der2c.derp2.derp2
der2c.derp1.derp2 <- BITS$der2c.derp1.derp2
der2c.derp1.derrho <- BITS$der2c.derp1.derrho
der2c.derp2.derrho <- BITS$der2c.derp2.derrho
der2pdf1.dereta1 <- dHs1$der2pdf2.dereta2
der2pdf2.dereta2 <- dHs2$der2pdf2.dereta2
der2pdf1.dersigma21.st2 <- dHs1$der2pdf2.dersigma2.st2
der2pdf2.dersigma22.st2 <- dHs2$der2pdf2.dersigma2.st2
der2p1.dereta1eta1 <- dHs1$der2p2.dereta2eta2
der2p2.dereta2eta2 <- dHs2$der2p2.dereta2eta2
der2p1.dersigma21.st2 <- dHs1$der2p2.dersigma2.st2
der2p2.dersigma22.st2 <- dHs2$der2p2.dersigma2.st2
der2pdf1.dereta1dersigma21.st <- dHs1$der2pdf2.dereta2dersigma2.st
der2pdf2.dereta2dersigma22.st <- dHs2$der2pdf2.dereta2dersigma2.st
der2p1.dereta1dersigma21.st <- dHs1$der2p2.dereta2dersigma2.st
der2p2.dereta2dersigma22.st <- dHs2$der2p2.dereta2dersigma2.st
der2teta.derteta.stteta.st <- BITS$der2teta.derteta.stteta.st
d2l.be1.be1.0 <- (der2pdf1.dereta1 * pdf1 - derpdf1.dereta1^2) / pdf1^2 +((der2c.derp1.derp1 * derp1.dereta1^2 + der2h.derp1p1 * der2p1.dereta1eta1) * c.copula2.be1be2 - derc.dereta1^2) /c.copula2.be1be2^2
d2l.be2.be2.0 <- (der2pdf2.dereta2 * pdf2 - derpdf2.dereta2^2) / pdf2^2 + ((der2c.derp2.derp2 * derp2.dereta2^2 + der2h.derp1p2 * der2p2.dereta2eta2) * c.copula2.be1be2 - derc.dereta2^2) /c.copula2.be1be2^2
d2l.rho.rho.0 <- ((der2c.derrho.derrho*derteta.derteta.st^2 + der2h.derp1teta *der2teta.derteta.stteta.st)*c.copula2.be1be2 -der2h.derp1teta.st^2) /c.copula2.be1be2^2
d2l.sigma21.sigma21.0 <- (der2pdf1.dersigma21.st2 * pdf1 - derpdf1.dersigma21.st^2) / pdf1^2 + ((der2c.derp1.derp1*derp1.dersigma21.st^2+der2h.derp1p1*der2p1.dersigma21.st2)*c.copula2.be1be2 - derc.dersigma21.st^2) /c.copula2.be1be2^2
d2l.sigma22.sigma22.0 <- (der2pdf2.dersigma22.st2 * pdf2 - derpdf2.dersigma22.st^2) / pdf2^2 + ((der2c.derp2.derp2*derp2.dersigma22.st^2+der2h.derp1p2*der2p2.dersigma22.st2)*c.copula2.be1be2 - derc.dersigma22.st^2) /c.copula2.be1be2^2
d2l.be1.be2.0 <- (der2c.derp1.derp2*derp1.dereta1*derp2.dereta2* c.copula2.be1be2 - derc.dereta1*derc.dereta2) /c.copula2.be1be2^2
d2l.be1.rho.0 <- (der2c.derp1.derrho *derp1.dereta1*derteta.derteta.st* c.copula2.be1be2 - derc.dereta1*der2h.derp1teta*derteta.derteta.st) /c.copula2.be1be2^2
d2l.be2.rho.0 <- (der2c.derp2.derrho *derp2.dereta2*derteta.derteta.st* c.copula2.be1be2 - derc.dereta2*der2h.derp1teta*derteta.derteta.st) /c.copula2.be1be2^2
d2l.be1.sigma21.0 <- (der2pdf1.dereta1dersigma21.st * pdf1 - derpdf1.dereta1*derpdf1.dersigma21.st) / pdf1^2 + ((der2c.derp1.derp1 * derp1.dereta1* derp1.dersigma21.st+der2h.derp1p1*der2p1.dereta1dersigma21.st) * c.copula2.be1be2 - derc.dereta1*derc.dersigma21.st) /c.copula2.be1be2^2
d2l.be2.sigma22.0 <- (der2pdf2.dereta2dersigma22.st * pdf2 - derpdf2.dereta2*derpdf2.dersigma22.st) / pdf2^2 + ((der2c.derp2.derp2 * derp2.dereta2* derp2.dersigma22.st+der2h.derp1p2*der2p2.dereta2dersigma22.st) * c.copula2.be1be2 - derc.dereta2*derc.dersigma22.st) /c.copula2.be1be2^2
d2l.be2.sigma21.0 <- (der2c.derp1.derp2*derp2.dereta2*derp1.dersigma21.st* c.copula2.be1be2 - derc.dereta2*derc.dersigma21.st)/c.copula2.be1be2^2
d2l.be1.sigma22.0 <- (der2c.derp1.derp2*derp1.dereta1*derp2.dersigma22.st* c.copula2.be1be2 - derc.dereta1*derc.dersigma22.st)/c.copula2.be1be2^2
d2l.rho.sigma21.0 <- (der2c.derp1.derrho*derp1.dersigma21.st*derteta.derteta.st*c.copula2.be1be2 - derc.dersigma21.st*der2h.derp1teta *derteta.derteta.st)/c.copula2.be1be2^2
d2l.rho.sigma22.0 <- (der2c.derp2.derrho*derp2.dersigma22.st*derteta.derteta.st*c.copula2.be1be2 - derc.dersigma22.st*der2h.derp1teta *derteta.derteta.st)/c.copula2.be1be2^2
d2l.sigma21.sigma22.0 <- (der2c.derp1.derp2*derp1.dersigma21.st*derp2.dersigma22.st* c.copula2.be1be2 - derc.dersigma21.st*derc.dersigma22.st ) /c.copula2.be1be2^2
d2l.be1.be1 <- -VC$weights*( d2.psi*dl.dbe1.0^2 +d.psi*d2l.be1.be1.0 )
d2l.be2.be2 <- -VC$weights*( d2.psi*dl.dbe2.0^2 +d.psi*d2l.be2.be2.0 )
d2l.rho.rho <- -VC$weights*( d2.psi*dl.dteta.st.0^2 +d.psi*d2l.rho.rho.0 )
d2l.sigma21.sigma21 <- -VC$weights*( d2.psi*dl.dsigma21.st.0^2 +d.psi*d2l.sigma21.sigma21.0)
d2l.sigma22.sigma22 <- -VC$weights*( d2.psi*dl.dsigma22.st.0^2 +d.psi*d2l.sigma22.sigma22.0)
d2l.be1.be2 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dbe2.0 +d.psi*d2l.be1.be2.0 )
d2l.be1.rho <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dteta.st.0 +d.psi*d2l.be1.rho.0 )
d2l.be2.rho <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dteta.st.0 +d.psi*d2l.be2.rho.0 )
d2l.be1.sigma21 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dsigma21.st.0 +d.psi*d2l.be1.sigma21.0 )
d2l.be2.sigma22 <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dsigma22.st.0 +d.psi*d2l.be2.sigma22.0 )
d2l.be2.sigma21 <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dsigma21.st.0 +d.psi*d2l.be2.sigma21.0 )
d2l.be1.sigma22 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dsigma22.st.0 +d.psi*d2l.be1.sigma22.0 )
d2l.rho.sigma21 <- -VC$weights*( d2.psi*dl.dteta.st.0*dl.dsigma21.st.0 +d.psi*d2l.rho.sigma21.0 )
d2l.rho.sigma22 <- -VC$weights*( d2.psi*dl.dteta.st.0*dl.dsigma22.st.0 +d.psi*d2l.rho.sigma22.0 )
d2l.sigma21.sigma22 <- -VC$weights*( d2.psi*dl.dsigma21.st.0*dl.dsigma22.st.0 +d.psi*d2l.sigma21.sigma22.0)
if( is.null(VC$X3) ){
G <- -c(colSums( c(dl.dbe1)*VC$X1 ),
colSums( c(dl.dbe2)*VC$X2 ),
sum( dl.dsigma21.st ),
sum( dl.dsigma22.st ),
sum( dl.dteta.st ) )
be1.be1 <- crossprod(VC$X1*c(d2l.be1.be1),VC$X1)
be2.be2 <- crossprod(VC$X2*c(d2l.be2.be2),VC$X2)
be1.be2 <- crossprod(VC$X1*c(d2l.be1.be2),VC$X2)
be1.rho <- t(t(rowSums(t(VC$X1*c(d2l.be1.rho)))))
be1.sigma21 <- t(t(rowSums(t(VC$X1*c(d2l.be1.sigma21)))))
be1.sigma22 <- t(t(rowSums(t(VC$X1*c(d2l.be1.sigma22)))))
be2.rho <- t(t(rowSums(t(VC$X2*c(d2l.be2.rho)))))
be2.sigma21 <- t(t(rowSums(t(VC$X2*c(d2l.be2.sigma21)))))
be2.sigma22 <- t(t(rowSums(t(VC$X2*c(d2l.be2.sigma22)))))
H <- rbind( cbind( be1.be1 , be1.be2 , be1.sigma21, be1.sigma22, be1.rho ),
cbind( t(be1.be2) , be2.be2 , be2.sigma21, be2.sigma22, be2.rho ),
cbind( t(be1.sigma21) , t(be2.sigma21) , sum(d2l.sigma21.sigma21), sum(d2l.sigma21.sigma22), sum(d2l.rho.sigma21)),
cbind( t(be1.sigma22) , t(be2.sigma22) , sum(d2l.sigma21.sigma22), sum(d2l.sigma22.sigma22), sum(d2l.rho.sigma22)),
cbind( t(be1.rho) , t(be2.rho) , sum(d2l.rho.sigma21), sum(d2l.rho.sigma22), sum(d2l.rho.rho) )
)
}
if( !is.null(VC$X3) ){
G <- -c( colSums( c(dl.dbe1)*VC$X1 ) ,
colSums( c(dl.dbe2)*VC$X2 ) ,
colSums(c(dl.dsigma21.st)*VC$X3 ) ,
colSums(c(dl.dsigma22.st)*VC$X4 ) ,
colSums( c(dl.dteta.st)*VC$X5 ) )
be1.be1 <- crossprod(VC$X1*c(d2l.be1.be1),VC$X1)
be2.be2 <- crossprod(VC$X2*c(d2l.be2.be2),VC$X2)
be1.be2 <- crossprod(VC$X1*c(d2l.be1.be2),VC$X2)
be1.rho <- crossprod(VC$X1*c(d2l.be1.rho),VC$X5)
be2.rho <- crossprod(VC$X2*c(d2l.be2.rho),VC$X5)
be1.sigma21 <- crossprod(VC$X1*c(d2l.be1.sigma21),VC$X3)
be1.sigma22 <- crossprod(VC$X1*c(d2l.be1.sigma22),VC$X4)
be2.sigma21 <- crossprod(VC$X2*c(d2l.be2.sigma21),VC$X3)
be2.sigma22 <- crossprod(VC$X2*c(d2l.be2.sigma22),VC$X4)
sigma21.sigma21 <- crossprod(VC$X3*c(d2l.sigma21.sigma21),VC$X3)
sigma21.sigma22 <- crossprod(VC$X3*c(d2l.sigma21.sigma22),VC$X4)
rho.sigma21 <- crossprod(VC$X3*c(d2l.rho.sigma21),VC$X5)
sigma22.sigma22 <- crossprod(VC$X4*c(d2l.sigma22.sigma22),VC$X4)
rho.sigma22 <- crossprod(VC$X4*c(d2l.rho.sigma22),VC$X5)
rho.rho <- crossprod(VC$X5*c(d2l.rho.rho),VC$X5)
H <- rbind( cbind( be1.be1 , be1.be2 , be1.sigma21, be1.sigma22, be1.rho ),
cbind( t(be1.be2) , be2.be2 , be2.sigma21, be2.sigma22, be2.rho ),
cbind( t(be1.sigma21) , t(be2.sigma21) , sigma21.sigma21, sigma21.sigma22, rho.sigma21),
cbind( t(be1.sigma22) , t(be2.sigma22) , t(sigma21.sigma22), sigma22.sigma22, rho.sigma22),
cbind( t(be1.rho) , t(be2.rho) , t(rho.sigma21), t(rho.sigma22), rho.rho ) )
}
res <- -sum(l.par)
if(VC$extra.regI == "pC") H <- regH(H, type = 1)
S.h <- ps$S.h
if( length(S.h) != 1){
S.h1 <- 0.5*crossprod(params,S.h)%*%params
S.h2 <- S.h%*%params
} else S.h <- S.h1 <- S.h2 <- 0
S.res <- res
res <- S.res + S.h1
G <- G + S.h2
H <- H + S.h
if(VC$extra.regI == "sED") H <- regH(H, type = 2)
if( VC$margins[1] == "LN" || VC$margins[2] == "LN"){
if(VC$margins[1] == "LN") dHs1 <- distrHsAT(exp(respvec$y1), eta1, sigma21, 1, margin2=VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
if(VC$margins[2] == "LN") dHs2 <- distrHsAT(exp(respvec$y2), eta2, sigma22, 1, margin2=VC$margins[2], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
pdf1 <- dHs1$pdf2
pdf2 <- dHs2$pdf2
p1 <- dHs1$p2
p2 <- dHs2$p2
dH <- copgHsAT(p1, p2, teta, VC$BivD, Ln = TRUE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr, par2 = VC$dof)
c.copula2.be1be2 <- dH$c.copula2.be1be2
l.ln <- -sum( VC$weights*( log(pdf1) + log(pdf2) + log(c.copula2.be1be2) ) )
}
list(value=res, gradient=G, hessian=H, S.h=S.h, S.h1=S.h1, S.h2=S.h2, l=S.res, l.ln = l.ln, l.par=l.par, ps = ps,
eta1=eta1, eta2=eta2, etad=etad, etas1 = etas1, etas2 = etas2,
BivD=VC$BivD, p1 = p1, p2 = p2, pdf1 = pdf1, pdf2 = pdf2,
c.copula.be2 = c.copula.be2,
c.copula.be1 = c.copula.be1,
c.copula2.be1be2 = c.copula2.be1be2,
dl.dbe1 =dl.dbe1,
dl.dbe2 =dl.dbe2,
dl.dsigma21.st =dl.dsigma21.st,
dl.dsigma22.st =dl.dsigma22.st,
dl.dteta.st =dl.dteta.st)
}
KironmoyDas/KD-STAT0035-GMupdate documentation built on Feb. 15, 2021, 12:17 a.m.
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Defines functions bcontROB
Documented in bcontROB
bcontROB <- function(params, respvec, VC, ps, AT = FALSE){
p1 <- p2 <- pdf1 <- pdf2 <- c.copula.be2 <- c.copula.be1 <- c.copula2.be1be2 <- NA
eta1 <- VC$X1%*%params[1:VC$X1.d2]
eta2 <- VC$X2%*%params[(VC$X1.d2 + 1):(VC$X1.d2 + VC$X2.d2)]
etad <- etas1 <- etas2 <- l.ln <- NULL
if(is.null(VC$X3)){
sigma21.st <- etas1 <- params[(VC$X1.d2 + VC$X2.d2 + 1)]
sigma22.st <- etas2 <- params[(VC$X1.d2 + VC$X2.d2 + 2)]
teta.st <- etad <- params[(VC$X1.d2 + VC$X2.d2 + 3)]
}
if(!is.null(VC$X3)){
sigma21.st <- etas1 <- VC$X3%*%params[(VC$X1.d2 + VC$X2.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2)]
sigma22.st <- etas2 <- VC$X4%*%params[(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2)]
teta.st <- etad <- VC$X5%*%params[(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2 + 1):(VC$X1.d2 + VC$X2.d2 + VC$X3.d2 + VC$X4.d2 + VC$X5.d2)]
}
##################
## Transformations
##################
sstr1 <- esp.tr(sigma21.st, VC$margins[1])
sstr2 <- esp.tr(sigma22.st, VC$margins[2])
sigma21.st <- sstr1$vrb.st
sigma22.st <- sstr2$vrb.st
sigma21 <- sstr1$vrb
sigma22 <- sstr2$vrb
eta1 <- eta.tr(eta1, VC$margins[1])
eta2 <- eta.tr(eta2, VC$margins[2])
resT <- teta.tr(VC, teta.st)
teta.st <- resT$teta.st
teta <- resT$teta
##################
##################
dHs1 <- distrHs(respvec$y1, eta1, sigma21, sigma21.st, nu = 1, nu.st = 1, margin2=VC$margins[1], naive = FALSE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
dHs2 <- distrHs(respvec$y2, eta2, sigma22, sigma22.st, nu = 1, nu.st = 1, margin2=VC$margins[2], naive = FALSE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
pdf1 <- dHs1$pdf2
pdf2 <- dHs2$pdf2
p1 <- dHs1$p2
p2 <- dHs2$p2
dH <- copgHsAT(p1, p2, teta, VC$BivD, Ln = TRUE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr, par2 = VC$dof)
c.copula2.be1be2 <- dH$c.copula2.be1be2
l.par1 <- log(pdf1) + log(pdf2) + log(c.copula2.be1be2)
Robj.lpar <- llpsi(l.par1, VC$tc)
psi <- Robj.lpar$psi
d.psi <- Robj.lpar$d.psi
d2.psi <- Robj.lpar$d2.psi
l.par <- VC$weights*( psi )
##################
##################
derpdf1.dereta1 <- dHs1$derpdf2.dereta2
derpdf1.dersigma21.st <- dHs1$derpdf2.dersigma2.st
derpdf2.dereta2 <- dHs2$derpdf2.dereta2
derpdf2.dersigma22.st <- dHs2$derpdf2.dersigma2.st
derp1.dereta1 <- dHs1$derp2.dereta2
derp1.dersigma21.st <- dHs1$derp2.dersigma.st
derp2.dereta2 <- dHs2$derp2.dereta2
derp2.dersigma22.st <- dHs2$derp2.dersigma.st
BITS <- copgHsCont(p1, p2, teta, teta.st, VC$BivD, Cont = TRUE, par2 = VC$dof, nu.st = log(VC$dof - 2))
der2h.derp1p1 <- BITS$der2h.derp1p1
derc.dereta1 <- der2h.derp1p1 * derp1.dereta1
derc.dersigma21.st <- der2h.derp1p1 * derp1.dersigma21.st
der2h.derp1p2 <- BITS$der2h.derp1p2
derc.dereta2 <- der2h.derp1p2 * derp2.dereta2
derc.dersigma22.st <- der2h.derp1p2 * derp2.dersigma22.st
der2h.derp1teta <- BITS$der2h.derp1teta
derteta.derteta.st <- BITS$derteta.derteta.st
der2h.derp1teta.st <- der2h.derp1teta * derteta.derteta.st # new bit
dl.dbe1.0 <- derpdf1.dereta1/pdf1 + derc.dereta1/c.copula2.be1be2
dl.dbe2.0 <- derpdf2.dereta2/pdf2 + derc.dereta2/c.copula2.be1be2
dl.dsigma21.st.0 <- derpdf1.dersigma21.st/pdf1 + derc.dersigma21.st/c.copula2.be1be2
dl.dsigma22.st.0 <- derpdf2.dersigma22.st/pdf2 + derc.dersigma22.st/c.copula2.be1be2
dl.dteta.st.0 <- der2h.derp1teta.st/c.copula2.be1be2
dl.dbe1 <- VC$weights*( d.psi*dl.dbe1.0 )
dl.dbe2 <- VC$weights*( d.psi*dl.dbe2.0 )
dl.dsigma21.st <- VC$weights*( d.psi*dl.dsigma21.st.0 )
dl.dsigma22.st <- VC$weights*( d.psi*dl.dsigma22.st.0 )
dl.dteta.st <- VC$weights*( d.psi*dl.dteta.st.0 )
#################################################################################################
der2c.derrho.derrho <- BITS$der2c.derrho.derrho
der2c.derp1.derp1 <- BITS$der2c.derp1.derp1
der2c.derp2.derp2 <- BITS$der2c.derp2.derp2
der2c.derp1.derp2 <- BITS$der2c.derp1.derp2
der2c.derp1.derrho <- BITS$der2c.derp1.derrho
der2c.derp2.derrho <- BITS$der2c.derp2.derrho
der2pdf1.dereta1 <- dHs1$der2pdf2.dereta2
der2pdf2.dereta2 <- dHs2$der2pdf2.dereta2
der2pdf1.dersigma21.st2 <- dHs1$der2pdf2.dersigma2.st2
der2pdf2.dersigma22.st2 <- dHs2$der2pdf2.dersigma2.st2
der2p1.dereta1eta1 <- dHs1$der2p2.dereta2eta2
der2p2.dereta2eta2 <- dHs2$der2p2.dereta2eta2
der2p1.dersigma21.st2 <- dHs1$der2p2.dersigma2.st2
der2p2.dersigma22.st2 <- dHs2$der2p2.dersigma2.st2
der2pdf1.dereta1dersigma21.st <- dHs1$der2pdf2.dereta2dersigma2.st
der2pdf2.dereta2dersigma22.st <- dHs2$der2pdf2.dereta2dersigma2.st
der2p1.dereta1dersigma21.st <- dHs1$der2p2.dereta2dersigma2.st
der2p2.dereta2dersigma22.st <- dHs2$der2p2.dereta2dersigma2.st
der2teta.derteta.stteta.st <- BITS$der2teta.derteta.stteta.st
d2l.be1.be1.0 <- (der2pdf1.dereta1 * pdf1 - derpdf1.dereta1^2) / pdf1^2 +((der2c.derp1.derp1 * derp1.dereta1^2 + der2h.derp1p1 * der2p1.dereta1eta1) * c.copula2.be1be2 - derc.dereta1^2) /c.copula2.be1be2^2
d2l.be2.be2.0 <- (der2pdf2.dereta2 * pdf2 - derpdf2.dereta2^2) / pdf2^2 + ((der2c.derp2.derp2 * derp2.dereta2^2 + der2h.derp1p2 * der2p2.dereta2eta2) * c.copula2.be1be2 - derc.dereta2^2) /c.copula2.be1be2^2
d2l.rho.rho.0 <- ((der2c.derrho.derrho*derteta.derteta.st^2 + der2h.derp1teta *der2teta.derteta.stteta.st)*c.copula2.be1be2 -der2h.derp1teta.st^2) /c.copula2.be1be2^2
d2l.sigma21.sigma21.0 <- (der2pdf1.dersigma21.st2 * pdf1 - derpdf1.dersigma21.st^2) / pdf1^2 + ((der2c.derp1.derp1*derp1.dersigma21.st^2+der2h.derp1p1*der2p1.dersigma21.st2)*c.copula2.be1be2 - derc.dersigma21.st^2) /c.copula2.be1be2^2
d2l.sigma22.sigma22.0 <- (der2pdf2.dersigma22.st2 * pdf2 - derpdf2.dersigma22.st^2) / pdf2^2 + ((der2c.derp2.derp2*derp2.dersigma22.st^2+der2h.derp1p2*der2p2.dersigma22.st2)*c.copula2.be1be2 - derc.dersigma22.st^2) /c.copula2.be1be2^2
d2l.be1.be2.0 <- (der2c.derp1.derp2*derp1.dereta1*derp2.dereta2* c.copula2.be1be2 - derc.dereta1*derc.dereta2) /c.copula2.be1be2^2
d2l.be1.rho.0 <- (der2c.derp1.derrho *derp1.dereta1*derteta.derteta.st* c.copula2.be1be2 - derc.dereta1*der2h.derp1teta*derteta.derteta.st) /c.copula2.be1be2^2
d2l.be2.rho.0 <- (der2c.derp2.derrho *derp2.dereta2*derteta.derteta.st* c.copula2.be1be2 - derc.dereta2*der2h.derp1teta*derteta.derteta.st) /c.copula2.be1be2^2
d2l.be1.sigma21.0 <- (der2pdf1.dereta1dersigma21.st * pdf1 - derpdf1.dereta1*derpdf1.dersigma21.st) / pdf1^2 + ((der2c.derp1.derp1 * derp1.dereta1* derp1.dersigma21.st+der2h.derp1p1*der2p1.dereta1dersigma21.st) * c.copula2.be1be2 - derc.dereta1*derc.dersigma21.st) /c.copula2.be1be2^2
d2l.be2.sigma22.0 <- (der2pdf2.dereta2dersigma22.st * pdf2 - derpdf2.dereta2*derpdf2.dersigma22.st) / pdf2^2 + ((der2c.derp2.derp2 * derp2.dereta2* derp2.dersigma22.st+der2h.derp1p2*der2p2.dereta2dersigma22.st) * c.copula2.be1be2 - derc.dereta2*derc.dersigma22.st) /c.copula2.be1be2^2
d2l.be2.sigma21.0 <- (der2c.derp1.derp2*derp2.dereta2*derp1.dersigma21.st* c.copula2.be1be2 - derc.dereta2*derc.dersigma21.st)/c.copula2.be1be2^2
d2l.be1.sigma22.0 <- (der2c.derp1.derp2*derp1.dereta1*derp2.dersigma22.st* c.copula2.be1be2 - derc.dereta1*derc.dersigma22.st)/c.copula2.be1be2^2
d2l.rho.sigma21.0 <- (der2c.derp1.derrho*derp1.dersigma21.st*derteta.derteta.st*c.copula2.be1be2 - derc.dersigma21.st*der2h.derp1teta *derteta.derteta.st)/c.copula2.be1be2^2
d2l.rho.sigma22.0 <- (der2c.derp2.derrho*derp2.dersigma22.st*derteta.derteta.st*c.copula2.be1be2 - derc.dersigma22.st*der2h.derp1teta *derteta.derteta.st)/c.copula2.be1be2^2
d2l.sigma21.sigma22.0 <- (der2c.derp1.derp2*derp1.dersigma21.st*derp2.dersigma22.st* c.copula2.be1be2 - derc.dersigma21.st*derc.dersigma22.st ) /c.copula2.be1be2^2
d2l.be1.be1 <- -VC$weights*( d2.psi*dl.dbe1.0^2 +d.psi*d2l.be1.be1.0 )
d2l.be2.be2 <- -VC$weights*( d2.psi*dl.dbe2.0^2 +d.psi*d2l.be2.be2.0 )
d2l.rho.rho <- -VC$weights*( d2.psi*dl.dteta.st.0^2 +d.psi*d2l.rho.rho.0 )
d2l.sigma21.sigma21 <- -VC$weights*( d2.psi*dl.dsigma21.st.0^2 +d.psi*d2l.sigma21.sigma21.0)
d2l.sigma22.sigma22 <- -VC$weights*( d2.psi*dl.dsigma22.st.0^2 +d.psi*d2l.sigma22.sigma22.0)
d2l.be1.be2 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dbe2.0 +d.psi*d2l.be1.be2.0 )
d2l.be1.rho <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dteta.st.0 +d.psi*d2l.be1.rho.0 )
d2l.be2.rho <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dteta.st.0 +d.psi*d2l.be2.rho.0 )
d2l.be1.sigma21 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dsigma21.st.0 +d.psi*d2l.be1.sigma21.0 )
d2l.be2.sigma22 <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dsigma22.st.0 +d.psi*d2l.be2.sigma22.0 )
d2l.be2.sigma21 <- -VC$weights*( d2.psi*dl.dbe2.0*dl.dsigma21.st.0 +d.psi*d2l.be2.sigma21.0 )
d2l.be1.sigma22 <- -VC$weights*( d2.psi*dl.dbe1.0*dl.dsigma22.st.0 +d.psi*d2l.be1.sigma22.0 )
d2l.rho.sigma21 <- -VC$weights*( d2.psi*dl.dteta.st.0*dl.dsigma21.st.0 +d.psi*d2l.rho.sigma21.0 )
d2l.rho.sigma22 <- -VC$weights*( d2.psi*dl.dteta.st.0*dl.dsigma22.st.0 +d.psi*d2l.rho.sigma22.0 )
d2l.sigma21.sigma22 <- -VC$weights*( d2.psi*dl.dsigma21.st.0*dl.dsigma22.st.0 +d.psi*d2l.sigma21.sigma22.0)
if( is.null(VC$X3) ){
G <- -c(colSums( c(dl.dbe1)*VC$X1 ),
colSums( c(dl.dbe2)*VC$X2 ),
sum( dl.dsigma21.st ),
sum( dl.dsigma22.st ),
sum( dl.dteta.st ) )
be1.be1 <- crossprod(VC$X1*c(d2l.be1.be1),VC$X1)
be2.be2 <- crossprod(VC$X2*c(d2l.be2.be2),VC$X2)
be1.be2 <- crossprod(VC$X1*c(d2l.be1.be2),VC$X2)
be1.rho <- t(t(rowSums(t(VC$X1*c(d2l.be1.rho)))))
be1.sigma21 <- t(t(rowSums(t(VC$X1*c(d2l.be1.sigma21)))))
be1.sigma22 <- t(t(rowSums(t(VC$X1*c(d2l.be1.sigma22)))))
be2.rho <- t(t(rowSums(t(VC$X2*c(d2l.be2.rho)))))
be2.sigma21 <- t(t(rowSums(t(VC$X2*c(d2l.be2.sigma21)))))
be2.sigma22 <- t(t(rowSums(t(VC$X2*c(d2l.be2.sigma22)))))
H <- rbind( cbind( be1.be1 , be1.be2 , be1.sigma21, be1.sigma22, be1.rho ),
cbind( t(be1.be2) , be2.be2 , be2.sigma21, be2.sigma22, be2.rho ),
cbind( t(be1.sigma21) , t(be2.sigma21) , sum(d2l.sigma21.sigma21), sum(d2l.sigma21.sigma22), sum(d2l.rho.sigma21)),
cbind( t(be1.sigma22) , t(be2.sigma22) , sum(d2l.sigma21.sigma22), sum(d2l.sigma22.sigma22), sum(d2l.rho.sigma22)),
cbind( t(be1.rho) , t(be2.rho) , sum(d2l.rho.sigma21), sum(d2l.rho.sigma22), sum(d2l.rho.rho) )
)
}
if( !is.null(VC$X3) ){
G <- -c( colSums( c(dl.dbe1)*VC$X1 ) ,
colSums( c(dl.dbe2)*VC$X2 ) ,
colSums(c(dl.dsigma21.st)*VC$X3 ) ,
colSums(c(dl.dsigma22.st)*VC$X4 ) ,
colSums( c(dl.dteta.st)*VC$X5 ) )
be1.be1 <- crossprod(VC$X1*c(d2l.be1.be1),VC$X1)
be2.be2 <- crossprod(VC$X2*c(d2l.be2.be2),VC$X2)
be1.be2 <- crossprod(VC$X1*c(d2l.be1.be2),VC$X2)
be1.rho <- crossprod(VC$X1*c(d2l.be1.rho),VC$X5)
be2.rho <- crossprod(VC$X2*c(d2l.be2.rho),VC$X5)
be1.sigma21 <- crossprod(VC$X1*c(d2l.be1.sigma21),VC$X3)
be1.sigma22 <- crossprod(VC$X1*c(d2l.be1.sigma22),VC$X4)
be2.sigma21 <- crossprod(VC$X2*c(d2l.be2.sigma21),VC$X3)
be2.sigma22 <- crossprod(VC$X2*c(d2l.be2.sigma22),VC$X4)
sigma21.sigma21 <- crossprod(VC$X3*c(d2l.sigma21.sigma21),VC$X3)
sigma21.sigma22 <- crossprod(VC$X3*c(d2l.sigma21.sigma22),VC$X4)
rho.sigma21 <- crossprod(VC$X3*c(d2l.rho.sigma21),VC$X5)
sigma22.sigma22 <- crossprod(VC$X4*c(d2l.sigma22.sigma22),VC$X4)
rho.sigma22 <- crossprod(VC$X4*c(d2l.rho.sigma22),VC$X5)
rho.rho <- crossprod(VC$X5*c(d2l.rho.rho),VC$X5)
H <- rbind( cbind( be1.be1 , be1.be2 , be1.sigma21, be1.sigma22, be1.rho ),
cbind( t(be1.be2) , be2.be2 , be2.sigma21, be2.sigma22, be2.rho ),
cbind( t(be1.sigma21) , t(be2.sigma21) , sigma21.sigma21, sigma21.sigma22, rho.sigma21),
cbind( t(be1.sigma22) , t(be2.sigma22) , t(sigma21.sigma22), sigma22.sigma22, rho.sigma22),
cbind( t(be1.rho) , t(be2.rho) , t(rho.sigma21), t(rho.sigma22), rho.rho ) )
}
res <- -sum(l.par)
if(VC$extra.regI == "pC") H <- regH(H, type = 1)
S.h <- ps$S.h
if( length(S.h) != 1){
S.h1 <- 0.5*crossprod(params,S.h)%*%params
S.h2 <- S.h%*%params
} else S.h <- S.h1 <- S.h2 <- 0
S.res <- res
res <- S.res + S.h1
G <- G + S.h2
H <- H + S.h
if(VC$extra.regI == "sED") H <- regH(H, type = 2)
if( VC$margins[1] == "LN" || VC$margins[2] == "LN"){
if(VC$margins[1] == "LN") dHs1 <- distrHsAT(exp(respvec$y1), eta1, sigma21, 1, margin2=VC$margins[1], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
if(VC$margins[2] == "LN") dHs2 <- distrHsAT(exp(respvec$y2), eta2, sigma22, 1, margin2=VC$margins[2], min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr)
pdf1 <- dHs1$pdf2
pdf2 <- dHs2$pdf2
p1 <- dHs1$p2
p2 <- dHs2$p2
dH <- copgHsAT(p1, p2, teta, VC$BivD, Ln = TRUE, min.dn = VC$min.dn, min.pr = VC$min.pr, max.pr = VC$max.pr, par2 = VC$dof)
c.copula2.be1be2 <- dH$c.copula2.be1be2
l.ln <- -sum( VC$weights*( log(pdf1) + log(pdf2) + log(c.copula2.be1be2) ) )
}
list(value=res, gradient=G, hessian=H, S.h=S.h, S.h1=S.h1, S.h2=S.h2, l=S.res, l.ln = l.ln, l.par=l.par, ps = ps,
eta1=eta1, eta2=eta2, etad=etad, etas1 = etas1, etas2 = etas2,
BivD=VC$BivD, p1 = p1, p2 = p2, pdf1 = pdf1, pdf2 = pdf2,
c.copula.be2 = c.copula.be2,
c.copula.be1 = c.copula.be1,
c.copula2.be1be2 = c.copula2.be1be2,
dl.dbe1 =dl.dbe1,
dl.dbe2 =dl.dbe2,
dl.dsigma21.st =dl.dsigma21.st,
dl.dsigma22.st =dl.dsigma22.st,
dl.dteta.st =dl.dteta.st)
}
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