Nothing
print.cjs <- function( x, alpha=c(0.05, 0.01), ... ){
nx <- x$aux$nx
ny <- x$aux$ny
cap.coef <- round(x$capcoef, 5)
sur.coef <- round(x$surcoef, 5)
se.cap <- round( x$se.capcoef, 5 )
se.sur <- round( x$se.surcoef, 5 )
if(nx > ny){
sur.coef<- c(sur.coef, rep("", nx-ny))
se.sur <- c(se.sur, rep("", nx-ny))
} else {
cap.coef<- c(cap.coef, rep("", ny-nx))
se.cap <- c(se.cap, rep("", ny-nx))
}
cat("Call:\n")
print(x$aux$call)
cat("\n")
cat(paste( format( c(" Capture var", names(cap.coef))),
format( c(" Est", cap.coef) ),
format( c(" SE", se.cap) ),
" ",
format( c(" Survival var", names(sur.coef))),
format( c(" Est", sur.coef) ),
format( c(" SE", se.sur) ),
"\n", sep=" "))
cat(paste("\nMessage =", x$message[2] ))
cat(paste("\nLink =", x$aux$link ))
cat(paste("\nModel df = ", x$df))
cat(paste("\nStd Errors and QAIC adjusted for C_hat = ", round(x$vif,6), "on", x$vif.df, "df"))
cat(paste("\nLog likelihood = ", x$loglike))
cat(paste("\nDeviance = ", x$dev))
cat(paste("\nAIC = ", x$aic))
cat(paste("\nAICc = ", x$aicc))
cat(paste("\nQAIC = ", x$qaic))
cat(paste("\nQAICc = ", x$qaicc))
#cat(paste("\nEBC = ", x$ebc, "\n"))
cat("\n")
if( inherits(x,"cjsgof") ){
# This object has goodness of fit results. Print them.
or.stars <- ifelse( x$or.pvalue <= alpha[2], "**", ifelse( x$or.pvalue <= alpha[1], "*", " "))
HL.stars <- ifelse( x$HL.pvalue <= alpha[2], "**", ifelse( x$HL.pvalue <= alpha[1], "*", " "))
mr.stars <- ifelse( x$gof.pvalue <= alpha[2], "**", ifelse( x$gof.pvalue <= alpha[1], "*", " "))
cat(paste("\nOverall goodness of fit results:\n"))
cat(paste( format( c(" ", " Osius-Rojek:", "Hosmer-Lemeshow:", " M&R ChiSquare:") ),
format( c("Statistic", round(x$or.chi, 4), round(x$HL.chi, 4), round(x$gof.chi, 4) )),
format( c("df", x$or.df, x$HL.df, x$gof.df )),
format( c("p", round(x$or.pvalue, 4), round(x$HL.pvalue, 4), round(x$gof.pvalue, 4) )),
format( c(" ", or.stars, HL.stars, mr.stars )),
"\n", sep="\t"))
roc.desc <- ifelse( x$roc < 0.7, "marginal discrimination",
ifelse( (0.7 <= x$roc) & (x$roc < 0.8), "acceptable discrimination",
ifelse( (0.8 <= x$roc) & (x$roc < 0.9), "excellent discrimination",
"outstanding discrimination")))
cat(paste(" ROC = ", round(x$roc, 4), ":", sep=""))
cat(paste("\t", roc.desc, "\n", sep=""))
cat(paste("\nTargeted lack of fit tests:\n"))
cat(paste( format( c(" ", " Occasion (Test 4):", "Individual (Test 5):") ),
format( c("ChiSquare", round(c(x$t4.chi, x$t5.chi), 3) )),
format( c("Df", x$t4.df, x$t5.df) ),
format( c("p", round(c(x$t4.pvalue, x$t5.pvalue), 4) )),
"\n", sep="\t"))
}
if(!is.null(x$n.hat)){
cat("\nPopulation Size Estimates (se):\n")
cat(paste( "N", 2:x$aux$ns , "=", round(x$n.hat[-1]), " (", round(x$se.n.hat[-1],2), "), ", sep=""))
cat("\n")
}
invisible()
}
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