Nothing
summary.nlFit <- function(object, ...) {
if (!inherits(object, "nlFit"))
stop("Object must belong to class nlFit")
if (!is.null(object$hessian)) {
varcov <- solve(object$hessian)
par.ses <- sqrt(diag(varcov))
object$sds <- par.ses
}
class(object) <- "summary.nlFit"
return(object)
}
print.summary.nlFit <- function(x,
digits = max(3, getOption("digits") - 3),
...) {
if (!inherits(x, "summary.nlFit"))
stop("Object must belong to class summary.nlFit")
cat("\nData: ", x$obsName, "\n")
cat("Parameter estimates:\n")
if (is.null(x$sds)) {
print.default(format(x$param, digits = digits),
print.gap = 2, quote = FALSE)
} else {
ans <- format(rbind(x$param, x$sds), digits = digits)
ans[1, ] <- sapply(ans[1, ], function(obs) paste("", obs))
ans[2, ] <- sapply(ans[2, ],
function(obs) paste("(", obs, ")", sep = ""))
dn <- dimnames(ans)
dn[[1]] <- rep("", 2)
dn[[2]] <-
paste(substring(" ", 1,
(nchar(ans[2, ]) - nchar(dn[[2]])) %/% 2), dn[[2]])
dn[[2]] <- paste(dn[[2]],
substring(" ", 1,
(nchar(ans[2, ]) - nchar(dn[[2]])) %/% 2))
dimnames(ans) <- dn
print.default(ans, print.gap = 2, quote = FALSE)
}
cat("Likelihood: ", x$maxLik, "\n")
cat("Method: ", x$method, "\n")
cat("Convergence code: ", x$conv, "\n")
cat("Iterations: ", x$iter, "\n")
invisible(x)
}
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