# R/summary.gamlss.r In JRM: Joint Regression Modelling

#### Documented in summary.gamlss

```summary.gamlss <- function(object, n.sim = 100, prob.lev = 0.05, ...){

bs <- SE <- Vb <- epds <- sigma2.st <- sigma2 <- nu.st <- nu <- est.RHOb <- XX <- Xt <- V <- 1

cont1par  <- c(object\$VC\$m1d, object\$VC\$bl)
cont2par  <- c(object\$VC\$m2,object\$VC\$m2d)
cont3par  <- c(object\$VC\$m3,object\$VC\$m3d)

n <- object\$n
epsilon <- 0.0000001; max.p   <- 0.9999999

lf <- length(object\$coefficients)

if(object\$VC\$surv.flex == FALSE) Vb <- object\$Vb else Vb <- object\$Vb.t

SE <- sqrt(diag(Vb))
bs <- rMVN(n.sim, mean = object\$coefficients, sigma=Vb) # this is not correct when surv.flex == TRUE but actually I need no sampling here for output so ok

#######
# CIs
#######

susutsnR <- susutsn(object, bs, lf, cont1par, cont2par, cont3par, prob.lev, type = "gamls")
CIsig2   <- susutsnR\$CIsig21
CInu     <- susutsnR\$CInu1

#########################

if(object\$VC\$gc.l == TRUE) gc()

susuR <- susu(object, SE, Vb)

tableN <- susuR\$tableN
table  <- susuR\$table

#########################

rm(bs, SE, Vb, XX, Xt, V)

res <- list(tableP1=table[[1]], tableP2=table[[2]], tableP3=table[[3]],
tableP4=table[[4]], tableP5=table[[5]], tableP6=table[[6]], tableP7=table[[7]], tableP8=table[[8]],
tableNP1=tableN[[1]], tableNP2=tableN[[2]], tableNP3=tableN[[3]],
tableNP4=tableN[[4]], tableNP5=tableN[[5]], tableNP6=tableN[[6]], tableNP7=tableN[[7]], tableNP8=tableN[[8]],
n=n,
sigma2=object\$sigma2,
nu=object\$nu,
sigma2.a=object\$sigma2.a,
nu.a=object\$nu.a,
formula = object\$formula,
formula1=object\$gam1\$formula, formula2=object\$gam2\$formula, formula3=object\$gam3\$formula,
formula4=object\$gam4\$formula, formula5=object\$gam5\$formula, formula6=object\$gam6\$formula,
formula7=object\$gam7\$formula, formula8=object\$gam8\$formula,
t.edf=object\$t.edf,
CIsig2=CIsig2, CInu=CInu,
margins = object\$margins,
l.sp1 = object\$l.sp1, l.sp2 = object\$l.sp2, l.sp3 = object\$l.sp3,
l.sp4 = object\$l.sp4, l.sp5 = object\$l.sp5, l.sp6 = object\$l.sp6,
l.sp7 = object\$l.sp7, l.sp8 = object\$l.sp8,
X2.null = is.null(object\$X2), univar.gamlss = TRUE, surv.flex = object\$surv.flex
)

class(res) <- "summary.gamlss"

res

}
```

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JRM documentation built on July 13, 2017, 5:03 p.m.