Nothing
qqplot <-
function(model, envelope=0.95, B=400)
{
resid = model$resid.stand
n = length(resid)
np = model$np
nq = model$nq
d = model$d
m = max(np,nq)
index1 = model$index1
index2 = model$index2
mu = model$fitted.values
varphi = model$dispersion
scalevar = model$scalevariance
dist = model$family
fixed = model$fixed
X = model$xreg
hat = model$coefficients
ar = ma = NULL
if(length(hat)==(np+nq))
{ if(np!=0) ar[1:np] = hat[1:np]
if(np!=0 && nq!=0) ma[1:nq] = hat[(np+1):(np+nq)]
if(np==0 && nq!=0) ma[1:nq] = hat[1:nq]
}
else
{ if(np!=0) ar[1:np] = hat[(NCOL(X)+1):(NCOL(X)+np)]
if(np!=0 && nq!=0) ma[1:nq] = hat[(NCOL(X)+np+1):(NCOL(X)+np+nq)]
if(np==0 && nq!=0) ma[1:nq] = hat[(NCOL(X)+1):(NCOL(X)+nq)]
}
resp<-NULL
e <- matrix(0,(n-m),B)
if(dist=="Normal") dist.theo <- rnorm(1000,0,1)
if(dist=="Student") dist.theo <- rt(1000,df=index1)
if(dist=="Gstudent")
{ z <- rnorm(1000,0,1)
T <- 1/rgamma(1000, shape = index1/2, rate = index2/2)
dist.theo <- T^(-0.5)*z
}
if(dist=="ExpPower")
{ v <- runif(1000,-1,1)
w <- rgamma(1000,shape=(1+(1+index1)/2))
dist.theo <- (2*w)^((1+index1)/2)*v
}
if(dist=="LogisticII")
{ v <- runif(1000,0,1)
dist.theo <- log(v/(1-v))
}
if(dist=="Cauchy")
{ v <- rnorm(1000,0,1)
w <- rnorm(1000,0,1)
dist.theo <- v/w
}
if(dist=="LogisticI")
stop(paste("Function not implemented for Logistic I distribution"))
if(dist=="Glogistic")
stop(paste("Function not implemented for Generalized Logistic distribution"))
if(dist=="Cnormal")
stop(paste("Function not implemented for Contamined Normal distribution"))
if(envelope!="FALSE")
{ for(i in 1:B)
{ resp <- symarma.sim(model=list(ar=ar,ma=ma),n=n,family=dist,index1,index2,varphi=1/scalevar)
fit.s <- elliptical.ts(resp,order=c(np,d,nq),xreg= X[(m+1):(n+m),],include.mean=FALSE,index1=index1,index2=index2,family=dist,trace=FALSE,fixed=fixed)
td <- fit.s$resid.stand
e[,i] <- sort(td)
e1 <- numeric(n-m)
e2 <- numeric(n-m)
for(i in 1:(n-m))
{ eo <- sort(e[i,])
e1[i] <- eo[ceiling(B*(1-envelope))]
e2[i] <- eo[ceiling(B*envelope)]
}
med <- apply(e,1,mean)
}
faixa <- range(resid,e1,e2)
}
if(envelope=="FALSE") faixa <- range(resid)
par(pty="s")
if(dist=="Normal")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for Normal"),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="Student")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {Student-t}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="Gstudent")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {Generalized-Student-t}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="ExpPower")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {ExpPower}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="LogisticI")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {LogisticI}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="LogisticII")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {LogisticII}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(dist=="Cauchy")
stats::qqplot(dist.theo,resid,main = expression("Q-Q plot for" ~~ {Cauchy}),xlab="Theorical Quantiles",ylab="Standardized residuals",xlim=range(dist.theo), ylim=faixa, pch=16)
if(envelope!="FALSE")
{ par(new=TRUE)
stats::qqplot(dist.theo,e1,axes=F,main="",xlab="",ylab="",type="l",xlim=range(dist.theo),ylim=faixa,lty=1)
par(new=TRUE)
stats::qqplot(dist.theo,e2,axes=F,main="",xlab="",ylab="", type="l",xlim=range(dist.theo),ylim=faixa,lty=1)
par(new=TRUE)
stats::qqplot(dist.theo,med,axes=F,main="",xlab="", ylab="", type="l",xlim=range(dist.theo),ylim=faixa,lty=2)
}
}
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