R/print.jointNestedPenal.R
In socale/frailtypack: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
#' Print a Short Summary of parameter estimates of a joint nested frailty model
#'
#' Prints a short summary of parameter estimates of a joint nested frailty
#' model, or more generally an object of class 'jointNestedPenal' for joint
#' nested frailty models.
#'
#'
#' @usage \method{print}{jointNestedPenal}(x, digits = max(options()$digits - 4,
#' 6), ...)
#' @param x the result of a call to the jointNestedPenal function
#' @param digits number of digits to print
#' @param \dots other unused arguments
#' @return
#'
#' Print, separately for each type of event (recurrent and terminal), the
#' parameter estimates of the survival or hazard functions.
#' @seealso \code{\link{frailtyPenal}}
#' @keywords methods
##' @export
"print.jointNestedPenal" <- function (x, digits = max(options()$digits - 4, 6), ...){
if (!is.null(cl <- x$call)){
cat("Call:\n")
dput(cl)
if (x$AG == TRUE) cat("\n Calendar timescale")
#if (x$intcens == TRUE) cat("\n interval censored data used")
}
cat("\n")
savedig <- options(digits = digits)
on.exit(options(savedig))
coef <- x$coef
nvar <- sum(x$nvar)
if (is.null(coef)){
x$varH<-matrix(x$varH)
x$varHIH<-matrix(x$varHIH)
}
if (x$typeof == 0){
if (x$n.knots.temp < 4){
cat("\n")
cat(" The minimum number of knots is 4","\n")
cat("\n")
}
if (x$n.knots.temp > 20){
cat("\n")
cat(" The maximum number of knots is 20","\n")
}
}
frail1 <- x$theta
frail2 <- x$eta
indic_alpha <- x$indic_alpha
indic_xi <- x$indic_ksi
if (x$istop == 1){
if (!is.null(coef)){
if (indic_alpha == 1 & indic_xi == 1){
seH <- sqrt(diag(x$varH))[-c(1:4)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:4)]
}
if (indic_alpha == 0 | indic_xi == 0) {
seH <- sqrt(diag(x$varH))[-c(1:3)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:3)]
}
if(indic_alpha == 0 & indic_xi == 0) {
seH <- sqrt(diag(x$varH))[-c(1:2)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:2)]
}
if (x$typeof == 0){
tmp <- cbind(coef, exp(coef), seH, seHIH, coef/seH, ifelse(signif(1 - pchisq((coef/seH)^2, 1), digits - 1) == 0, "< 1e-16", signif(1 - pchisq((coef/seH)^2, 1), digits - 1)))
if(x$global_chisq.test==1) tmpwald <- cbind(x$global_chisq, x$dof_chisq, ifelse(x$p.global_chisq == 0, "< 1e-16", x$p.global_chisq))
if(x$global_chisq.test_d==1) tmpwalddc <- cbind(x$global_chisq_d, x$dof_chisq_d, ifelse(x$p.global_chisq_d == 0, "< 1e-16", x$p.global_chisq_d))
}
else{
tmp <- cbind(coef, exp(coef), seH, coef/seH, ifelse(signif(1 - pchisq((coef/seH)^2, 1), digits - 1) == 0, "< 1e-16", signif(1 - pchisq((coef/seH)^2, 1), digits - 1)))
if(x$global_chisq.test==1) tmpwald <- cbind(x$global_chisq, x$dof_chisq, ifelse(x$p.global_chisq == 0, "< 1e-16", x$p.global_chisq))
if(x$global_chisq.test_d==1) tmpwalddc <- cbind(x$global_chisq_d, x$dof_chisq_d, ifelse(x$p.global_chisq_d == 0, "< 1e-16", x$p.global_chisq_d))
}
cat("\n")
cat(" Joint nested gamma frailty model for recurrent and a terminal event processes","\n")
if (x$typeof == 0) cat(" using a Penalized Likelihood on the hazard function","\n")
else cat(" using a Parametrical approach for the hazard function","\n")
if (x$n.strat>1) cat(" (Stratification structure used for recurrences) :",x$n.strat,"strata \n")
if (x$typeof == 0){
if(x$global_chisq.test==1) dimnames(tmpwald) <- list(x$names.factor,c("chisq", "df", "global p"))
if(x$global_chisq.test_d==1) dimnames(tmpwalddc) <- list(x$names.factordc,c("chisq", "df", "global p"))
dimnames(tmp) <- list(names(coef), c("coef", "exp(coef)","SE coef (H)", "SE coef (HIH)", "z", "p"))
}else{
if(x$global_chisq.test==1) dimnames(tmpwald) <- list(x$names.factor,c("chisq", "df", "global p"))
if(x$global_chisq.test_d==1) dimnames(tmpwalddc) <- list(x$names.factordc,c("chisq", "df", "global p"))
dimnames(tmp) <- list(names(coef), c("coef", "exp(coef)","SE coef (H)", "z", "p"))
}
cat("\n")
if (x$noVar1 == 0){
cat("Recurrences:\n")
cat("------------- \n")
prmatrix(tmp[1:x$nvar[1], ,drop=FALSE])
if(x$global_chisq.test==1){
cat("\n")
prmatrix(tmpwald)
}
}
cat("\n")
if (x$noVar2 == 0){
cat("Terminal event:\n")
cat("---------------- \n")
prmatrix(tmp[-c(1:x$nvar[1]), ,drop=FALSE])
if(x$global_chisq.test_d==1){
cat("\n")
prmatrix(tmpwalddc)
}
}
cat("\n")
}
temp1 <- diag(x$varH)[1]
temp2 <- diag(x$varH)[2]
seH.frail1 <- sqrt(((2 * (frail1^0.5))^2) * temp1) # delta methode
seH.frail2 <- sqrt(((2 * (frail2^0.5))^2) * temp2)
temp1 <- diag(x$varHIH)[1]
temp2 <- diag(x$varHIH)[2]
seHIH.frail1 <- sqrt(((2 * (frail1^0.5))^2) * temp1) # delta methode
seHIH.frail1 <- sqrt(((2 * (frail2^0.5))^2) * temp2)
if (x$noVar1 == 1){
cat("\n")
cat(" Recurrences: No covariates \n")
cat(" ----------- \n")
}
if (x$noVar2 == 1){
cat("\n")
cat(" Terminal event: No covariates \n")
cat(" -------------- \n")
cat("\n")
}
cat(" Frailty parameters: \n")
cat(" theta (variance of Frailties, u):", frail1, "(SE (H):",seH.frail1, ")", "p =", ifelse(signif(1 - pnorm(frail1/seH.frail1), digits - 1) == 0, "< 1e-16", signif(1 - pnorm(frail1/seH.frail1), digits - 1)), "\n")
cat(" eta (variance of Frailties, w) :", frail2, "(SE (H) :", seH.frail2,")", "p =", ifelse(signif(1 - pnorm(frail2/seH.frail2), digits - 1) == 0, "< 1e-16", signif(1 - pnorm(frail2/seH.frail2), digits - 1)), "\n")
if (indic_alpha == 1) cat(" alpha (u^alpha for terminal event):", x$alpha, "(SE (H):",sqrt(diag(x$varH))[3], ")", "p =", ifelse(signif(1 - pchisq((x$alpha/sqrt(diag(x$varH))[3])^2,1), digits - 1) == 0,"< 1e-16", signif(1 - pchisq((x$alpha/sqrt(diag(x$varH))[3])^2,1), digits - 1)), "\n")
if (indic_xi == 1 & indic_alpha == 1) cat(" ksi (w^ksi for recurrent event):", x$ksi, "(SE (H):",sqrt(diag(x$varH))[4], ")", "p =", ifelse(signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[4])^2,1), digits - 1) == 0,"< 1e-16",signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[4])^2,1), digits - 1)), "\n")
if (indic_xi == 1 & indic_alpha == 0) cat(" ksi (w^ksi for recurrent event):", x$ksi, "(SE (H):",sqrt(diag(x$varH))[3], ")", "p =", ifelse(signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[3])^2,1), digits - 1) == 0,"< 1e-16", signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[3])^2,1), digits - 1)), "\n")
cat(" \n")
if (x$typeof == 0){
cat(paste(" penalized marginal log-likelihood =", round(x$logLikPenal,2)))
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" LCV = the approximate likelihood cross-validation criterion\n")
cat(" in the semi parametric case =",x$LCV,"\n")
}
else{
cat(paste(" marginal log-likelihood =", round(x$logLik,2)))
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" AIC = Aikaike information Criterion =",x$AIC,"\n")
cat("\n")
cat("The expression of the Aikaike Criterion is:","\n")
cat(" 'AIC = (1/n)[np - l(.)]'","\n")
if (x$typeof == 2){
cat("\n")
cat(" Scale for the weibull hazard function is :",round(x$scale.weib[1],2),round(x$scale.weib[2],2),"\n")
cat(" Shape for the weibull hazard function is :",round(x$shape.weib[1],2),round(x$shape.weib[2],2),"\n")
cat("\n")
cat("The expression of the Weibull hazard function is:","\n")
cat(" 'lambda(t) = (shape.(t^(shape-1)))/(scale^shape)'","\n")
cat("The expression of the Weibull survival function is:","\n")
cat(" 'S(t) = exp[- (t/scale)^shape]'")
cat("\n")
}
}
cat("\n")
cat(" n observations=", x$n, " n subjects=", x$subgroups, " n groups=", x$groups)
if (length(x$na.action)) cat(" (", length(x$na.action), " observation deleted due to missing) \n")
else cat("\n")
cat(" n recurrent events=", x$n.events)
cat("\n")
cat(" n terminal events=", x$n.death)
cat("\n")
cat(" n censored events=" ,x$n.censored)
cat("\n")
cat(" number of iterations: ", x$n.iter,"\n")
if (x$logNormal == 0) {
cat(" Number of nodes for the Gauss-Laguerre quadrature: ", x$nb.gl,"\n")
}
else {cat(" Number of nodes for the Gauss-Hermite quadrature: ", x$nb.gh,"\n")}
if (x$typeof == 0){ # splines
cat("\n")
cat(" Exact number of knots used: ", x$n.knots, "\n")
cat(" Value of the smoothing parameters: ", x$kappa, sep=" ")
cat("\n")
}
}else{ # s'il y a eu un pb de convergence et istop != 1
if (!is.null(coef)){
cat("\n")
cat(" Joint nested gamma frailty model for recurrent and a terminal event processes","\n")
if (x$typeof == 0) cat(" using a Penalized Likelihood on the hazard function","\n")
else cat(" using a Parametrical approach for the hazard function","\n")
if (x$noVar1 == 1){
cat("\n")
cat(" Recurrences: No covariates \n")
cat(" ----------- \n")
}
if (x$noVar2 == 1){
cat("\n")
cat(" Terminal event: No covariates \n")
cat(" -------------- \n")
cat("\n")
}
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" n observations=", x$n, " n subjects=", x$subgroups, " n families=", x$groups)
if (length(x$na.action)) cat(" (", length(x$na.action), " observation deleted due to missing) \n")
else cat("\n")
cat(" n recurrent events=", x$n.events)
cat("\n")
cat(" n terminal events=", x$n.death)
cat("\n")
cat(" n censored events=" ,x$n.censored)
cat("\n")
cat(" number of iterations: ", x$n.iter,"\n")
if (x$logNormal == 0) {
cat(" Number of nodes for the Gauss-Laguerre quadrature: ", x$nb.gl,"\n")
}
else {cat(" Number of nodes for the Gauss-Hermite quadrature: ", x$nb.gh,"\n")}
}
}
invisible()
}
socale/frailtypack documentation built on June 15, 2021, 3:37 a.m.
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#' Print a Short Summary of parameter estimates of a joint nested frailty model
#'
#' Prints a short summary of parameter estimates of a joint nested frailty
#' model, or more generally an object of class 'jointNestedPenal' for joint
#' nested frailty models.
#'
#'
#' @usage \method{print}{jointNestedPenal}(x, digits = max(options()$digits - 4,
#' 6), ...)
#' @param x the result of a call to the jointNestedPenal function
#' @param digits number of digits to print
#' @param \dots other unused arguments
#' @return
#'
#' Print, separately for each type of event (recurrent and terminal), the
#' parameter estimates of the survival or hazard functions.
#' @seealso \code{\link{frailtyPenal}}
#' @keywords methods
##' @export
"print.jointNestedPenal" <- function (x, digits = max(options()$digits - 4, 6), ...){
if (!is.null(cl <- x$call)){
cat("Call:\n")
dput(cl)
if (x$AG == TRUE) cat("\n Calendar timescale")
#if (x$intcens == TRUE) cat("\n interval censored data used")
}
cat("\n")
savedig <- options(digits = digits)
on.exit(options(savedig))
coef <- x$coef
nvar <- sum(x$nvar)
if (is.null(coef)){
x$varH<-matrix(x$varH)
x$varHIH<-matrix(x$varHIH)
}
if (x$typeof == 0){
if (x$n.knots.temp < 4){
cat("\n")
cat(" The minimum number of knots is 4","\n")
cat("\n")
}
if (x$n.knots.temp > 20){
cat("\n")
cat(" The maximum number of knots is 20","\n")
}
}
frail1 <- x$theta
frail2 <- x$eta
indic_alpha <- x$indic_alpha
indic_xi <- x$indic_ksi
if (x$istop == 1){
if (!is.null(coef)){
if (indic_alpha == 1 & indic_xi == 1){
seH <- sqrt(diag(x$varH))[-c(1:4)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:4)]
}
if (indic_alpha == 0 | indic_xi == 0) {
seH <- sqrt(diag(x$varH))[-c(1:3)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:3)]
}
if(indic_alpha == 0 & indic_xi == 0) {
seH <- sqrt(diag(x$varH))[-c(1:2)]
seHIH <- sqrt(diag(x$varHIH))[-c(1:2)]
}
if (x$typeof == 0){
tmp <- cbind(coef, exp(coef), seH, seHIH, coef/seH, ifelse(signif(1 - pchisq((coef/seH)^2, 1), digits - 1) == 0, "< 1e-16", signif(1 - pchisq((coef/seH)^2, 1), digits - 1)))
if(x$global_chisq.test==1) tmpwald <- cbind(x$global_chisq, x$dof_chisq, ifelse(x$p.global_chisq == 0, "< 1e-16", x$p.global_chisq))
if(x$global_chisq.test_d==1) tmpwalddc <- cbind(x$global_chisq_d, x$dof_chisq_d, ifelse(x$p.global_chisq_d == 0, "< 1e-16", x$p.global_chisq_d))
}
else{
tmp <- cbind(coef, exp(coef), seH, coef/seH, ifelse(signif(1 - pchisq((coef/seH)^2, 1), digits - 1) == 0, "< 1e-16", signif(1 - pchisq((coef/seH)^2, 1), digits - 1)))
if(x$global_chisq.test==1) tmpwald <- cbind(x$global_chisq, x$dof_chisq, ifelse(x$p.global_chisq == 0, "< 1e-16", x$p.global_chisq))
if(x$global_chisq.test_d==1) tmpwalddc <- cbind(x$global_chisq_d, x$dof_chisq_d, ifelse(x$p.global_chisq_d == 0, "< 1e-16", x$p.global_chisq_d))
}
cat("\n")
cat(" Joint nested gamma frailty model for recurrent and a terminal event processes","\n")
if (x$typeof == 0) cat(" using a Penalized Likelihood on the hazard function","\n")
else cat(" using a Parametrical approach for the hazard function","\n")
if (x$n.strat>1) cat(" (Stratification structure used for recurrences) :",x$n.strat,"strata \n")
if (x$typeof == 0){
if(x$global_chisq.test==1) dimnames(tmpwald) <- list(x$names.factor,c("chisq", "df", "global p"))
if(x$global_chisq.test_d==1) dimnames(tmpwalddc) <- list(x$names.factordc,c("chisq", "df", "global p"))
dimnames(tmp) <- list(names(coef), c("coef", "exp(coef)","SE coef (H)", "SE coef (HIH)", "z", "p"))
}else{
if(x$global_chisq.test==1) dimnames(tmpwald) <- list(x$names.factor,c("chisq", "df", "global p"))
if(x$global_chisq.test_d==1) dimnames(tmpwalddc) <- list(x$names.factordc,c("chisq", "df", "global p"))
dimnames(tmp) <- list(names(coef), c("coef", "exp(coef)","SE coef (H)", "z", "p"))
}
cat("\n")
if (x$noVar1 == 0){
cat("Recurrences:\n")
cat("------------- \n")
prmatrix(tmp[1:x$nvar[1], ,drop=FALSE])
if(x$global_chisq.test==1){
cat("\n")
prmatrix(tmpwald)
}
}
cat("\n")
if (x$noVar2 == 0){
cat("Terminal event:\n")
cat("---------------- \n")
prmatrix(tmp[-c(1:x$nvar[1]), ,drop=FALSE])
if(x$global_chisq.test_d==1){
cat("\n")
prmatrix(tmpwalddc)
}
}
cat("\n")
}
temp1 <- diag(x$varH)[1]
temp2 <- diag(x$varH)[2]
seH.frail1 <- sqrt(((2 * (frail1^0.5))^2) * temp1) # delta methode
seH.frail2 <- sqrt(((2 * (frail2^0.5))^2) * temp2)
temp1 <- diag(x$varHIH)[1]
temp2 <- diag(x$varHIH)[2]
seHIH.frail1 <- sqrt(((2 * (frail1^0.5))^2) * temp1) # delta methode
seHIH.frail1 <- sqrt(((2 * (frail2^0.5))^2) * temp2)
if (x$noVar1 == 1){
cat("\n")
cat(" Recurrences: No covariates \n")
cat(" ----------- \n")
}
if (x$noVar2 == 1){
cat("\n")
cat(" Terminal event: No covariates \n")
cat(" -------------- \n")
cat("\n")
}
cat(" Frailty parameters: \n")
cat(" theta (variance of Frailties, u):", frail1, "(SE (H):",seH.frail1, ")", "p =", ifelse(signif(1 - pnorm(frail1/seH.frail1), digits - 1) == 0, "< 1e-16", signif(1 - pnorm(frail1/seH.frail1), digits - 1)), "\n")
cat(" eta (variance of Frailties, w) :", frail2, "(SE (H) :", seH.frail2,")", "p =", ifelse(signif(1 - pnorm(frail2/seH.frail2), digits - 1) == 0, "< 1e-16", signif(1 - pnorm(frail2/seH.frail2), digits - 1)), "\n")
if (indic_alpha == 1) cat(" alpha (u^alpha for terminal event):", x$alpha, "(SE (H):",sqrt(diag(x$varH))[3], ")", "p =", ifelse(signif(1 - pchisq((x$alpha/sqrt(diag(x$varH))[3])^2,1), digits - 1) == 0,"< 1e-16", signif(1 - pchisq((x$alpha/sqrt(diag(x$varH))[3])^2,1), digits - 1)), "\n")
if (indic_xi == 1 & indic_alpha == 1) cat(" ksi (w^ksi for recurrent event):", x$ksi, "(SE (H):",sqrt(diag(x$varH))[4], ")", "p =", ifelse(signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[4])^2,1), digits - 1) == 0,"< 1e-16",signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[4])^2,1), digits - 1)), "\n")
if (indic_xi == 1 & indic_alpha == 0) cat(" ksi (w^ksi for recurrent event):", x$ksi, "(SE (H):",sqrt(diag(x$varH))[3], ")", "p =", ifelse(signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[3])^2,1), digits - 1) == 0,"< 1e-16", signif(1 - pchisq((x$ksi/sqrt(diag(x$varH))[3])^2,1), digits - 1)), "\n")
cat(" \n")
if (x$typeof == 0){
cat(paste(" penalized marginal log-likelihood =", round(x$logLikPenal,2)))
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" LCV = the approximate likelihood cross-validation criterion\n")
cat(" in the semi parametric case =",x$LCV,"\n")
}
else{
cat(paste(" marginal log-likelihood =", round(x$logLik,2)))
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" AIC = Aikaike information Criterion =",x$AIC,"\n")
cat("\n")
cat("The expression of the Aikaike Criterion is:","\n")
cat(" 'AIC = (1/n)[np - l(.)]'","\n")
if (x$typeof == 2){
cat("\n")
cat(" Scale for the weibull hazard function is :",round(x$scale.weib[1],2),round(x$scale.weib[2],2),"\n")
cat(" Shape for the weibull hazard function is :",round(x$shape.weib[1],2),round(x$shape.weib[2],2),"\n")
cat("\n")
cat("The expression of the Weibull hazard function is:","\n")
cat(" 'lambda(t) = (shape.(t^(shape-1)))/(scale^shape)'","\n")
cat("The expression of the Weibull survival function is:","\n")
cat(" 'S(t) = exp[- (t/scale)^shape]'")
cat("\n")
}
}
cat("\n")
cat(" n observations=", x$n, " n subjects=", x$subgroups, " n groups=", x$groups)
if (length(x$na.action)) cat(" (", length(x$na.action), " observation deleted due to missing) \n")
else cat("\n")
cat(" n recurrent events=", x$n.events)
cat("\n")
cat(" n terminal events=", x$n.death)
cat("\n")
cat(" n censored events=" ,x$n.censored)
cat("\n")
cat(" number of iterations: ", x$n.iter,"\n")
if (x$logNormal == 0) {
cat(" Number of nodes for the Gauss-Laguerre quadrature: ", x$nb.gl,"\n")
}
else {cat(" Number of nodes for the Gauss-Hermite quadrature: ", x$nb.gh,"\n")}
if (x$typeof == 0){ # splines
cat("\n")
cat(" Exact number of knots used: ", x$n.knots, "\n")
cat(" Value of the smoothing parameters: ", x$kappa, sep=" ")
cat("\n")
}
}else{ # s'il y a eu un pb de convergence et istop != 1
if (!is.null(coef)){
cat("\n")
cat(" Joint nested gamma frailty model for recurrent and a terminal event processes","\n")
if (x$typeof == 0) cat(" using a Penalized Likelihood on the hazard function","\n")
else cat(" using a Parametrical approach for the hazard function","\n")
if (x$noVar1 == 1){
cat("\n")
cat(" Recurrences: No covariates \n")
cat(" ----------- \n")
}
if (x$noVar2 == 1){
cat("\n")
cat(" Terminal event: No covariates \n")
cat(" -------------- \n")
cat("\n")
}
cat("\n")
cat(" Convergence criteria: \n")
cat(" parameters =",signif(x$EPS[1],3),"likelihood =",signif(x$EPS[2],3),"gradient =",signif(x$EPS[3],3),"\n")
cat("\n")
cat(" n observations=", x$n, " n subjects=", x$subgroups, " n families=", x$groups)
if (length(x$na.action)) cat(" (", length(x$na.action), " observation deleted due to missing) \n")
else cat("\n")
cat(" n recurrent events=", x$n.events)
cat("\n")
cat(" n terminal events=", x$n.death)
cat("\n")
cat(" n censored events=" ,x$n.censored)
cat("\n")
cat(" number of iterations: ", x$n.iter,"\n")
if (x$logNormal == 0) {
cat(" Number of nodes for the Gauss-Laguerre quadrature: ", x$nb.gl,"\n")
}
else {cat(" Number of nodes for the Gauss-Hermite quadrature: ", x$nb.gh,"\n")}
}
}
invisible()
}
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