Nothing
print.summary.moult <- function(x, digits = max(3, getOption("digits") - 3), ...)
{ cat("\nCall:", deparse(x$call, width.cutoff = floor(getOption("width") *
0.85)), "", sep = "\n")
if (!x$converged) {
cat("model did not converge\n")
}
else {
n.d <- length(x$coefficients$duration)
n.m <- length(x$coefficients$mean)
n.s <- length(x$coefficients$sd)
n.par <- n.d + n.m + n.s
coefmat <- data.frame(unlist(x$coefficients), unlist(x$standard.errors))
names(coefmat) <- c("Estimate", "Std. Error")
# rownames(coefmat) <- c(names(x$coefficients$duration), names(x$coefficients$mean),
# names(x$coefficients$sd))
cat("\nDuration coefficients:\n")
d.mat <- coefmat[(1:n.d), ]
rownames(d.mat) <- names(x$coefficients$duration)
printCoefmat(d.mat, digits = digits, signif.legend = FALSE)
cat("\nMean start date coefficients:\n")
m.mat <- coefmat[(n.d + 1):(n.d + n.m), ]
rownames(m.mat) <- names(x$coefficients$mean)
printCoefmat(m.mat, digits = digits, signif.legend = FALSE)
cat("\nCoefficients for standard deviation in start date:\n")
sd.mat <- coefmat[(n.d + n.m + 1):(n.par), ]
rownames(sd.mat) <- names(x$coefficients$sd)
printCoefmat(sd.mat, digits = digits, signif.legend = FALSE)
cat("\nLog-likelihood:", formatC(x$loglik, digits = digits),
"on", x$n - x$df.residual, "Df\n")
}
invisible(x)
}
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