# R/Profile_likelihood_cd_nm_joint_D_KT.R In texmex: Statistical Modelling of Extreme Values

```Profile_likelihood_cd_nm_joint_D_KT <-
function (par,listr,x,
Zestfun,...,v,
silly=-10^(40))
{
n                <- NULL
sig              <- NULL
sumX             <- NULL
no_of_roots      <- NULL
no_of_roots_star <- NULL
temp             <- NULL
Zq               <- NULL
Zstarq           <- NULL
xstar            <- NULL
xdstar           <- NULL
s                <- NULL
cond_alphas      <- NULL
cond_ord_dep     <- NULL
cond_ord_pairs   <- NULL
vdep             <- NULL
z                <- list()
Pl               <- silly
X                <- vector('list',length(listr))
Y                <- vector('list',length(listr))
Z                <- vector('list',length(listr))
Zstar            <- vector('list',length(listr))
index_alpha      <- seq(1,((2*(length(listr)) ) -1),by=2)
index_beta       <- seq(2,((2*(length(listr)) )   ),by=2)
alpha            <- par[index_alpha]
beta             <- par[index_beta]
xstar            <- rep(v,(length(listr)-1))
xdstar           <- rep(v,(length(listr)-1))
xdepstar         <- rep(vdep,length(listr))

for(i in 1:length(listr))
{
cond_alphas[i] <- ((alpha[i]) <= 1)
temp           <- as.matrix(listr[[i]])
X[[i]]         <- temp[,1][temp[,1]>x]
vdep[i]        <- max(X[[i]])
n[i]           <- length(X[[i]])
Y[[i]]         <- temp[,2][temp[,1]>x]
Z[[i]]         <- (Y[[i]] - alpha[i]*X[[i]])/(X[[i]]^beta[i])
Zstar[[i]]     <- (Y[[i]] - X[[i]])
Zq[i]          <- Zestfun(Z[[i]],...)
Zstarq[i]      <- Zestfun(Zstar[[i]],...)
sig[i]         <- (1/n[i]) * sum ((Z[[i]]-mean(Z[[i]]))^2)
sumX[i]        <- sum(beta[i]*log(X[[i]]))
}

if(all(cond_alphas==TRUE))
{
for(i in 1:length(listr))
{
temp_roots_star      <- roots(lev=v,a=1,c=alpha[i],
b=0,d=beta[i],Zj=Zstarq[i],
Zk=Zq[i])
xdepstar[i]          <- temp_roots_star\$xstar
}
}

if(all(alpha <= 1) & all(alpha >= -1) & all(beta < 1) &
all(cond_alphas==TRUE))
{
for(j in 1:length(listr))
{
cond_ord_dep[j] <-  ((alpha[j]) <=
#mark2:change v to vdep[j]
(min(1,(Dcond(v,1,0,alpha[j],beta[j],
Zstarq[j],Zq[j])),#-(1e-10)),
(Dcond(xdepstar[j],1,0,alpha[j],
beta[j],Zstarq[j],
Zq[j])))))#-(1e-10)) )))
}

condition <- (all(cond_ord_dep==TRUE))

if( condition == TRUE )
{
Pl  <- sum(((-(n/2)*log (2*pi*sig)) - sumX - (n/2))) # note sig is actually sigmaSquared in the normal density
}
if(condition == FALSE)
{
Pl  <- silly
}
}
if((all(alpha <= 1) ==FALSE) ||  (all(alpha >= -1)==FALSE) ||
(all(beta < 1)==FALSE) || (all(cond_alphas==TRUE)==FALSE))
{
Pl <- silly
}

z\$Pl <- Pl
#    z\$Zs <- Zstarq
#    z\$Zq <- Zq

return(z\$Pl)
}
```

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texmex documentation built on May 2, 2019, 5:41 a.m.