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#############################################################################
# Copyright (c) 2014 Mathieu Ribatet
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the
# Free Software Foundation, Inc.,
# 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA
#
#############################################################################
print.mcpot <- function(x, digits = max(3, getOption("digits") - 3), ...){
if (!inherits(x, "mcpot"))
stop("Use only with 'mcpot' objects")
cat("\nCall:", deparse(x$call), "\n")
cat("Estimator:", x$est, "\n")
if (x$model == "log")
model <- "Logistic"
if (x$model == "alog")
model <- "Asymetric Logistic"
if (x$model == "nlog")
model <- "Negative Logistic"
if (x$model == "anlog")
model <- "Asymetric Negative Logistic"
if (x$model == "mix")
model <- "Mixed"
if (x$model == "amix")
model <- "Asymetric Mixed"
cat("Dependence Model and Strenght:\n")
cat("\tModel :", model, "\n")
cat("\tlim_u Pr[ X_1 > u | X_2 > u] =", round(x$chi, 3),
"\n")
if (x$est == 'MLE'){
cat("Deviance:", x$deviance, "\n")
cat(" AIC:", AIC(x), "\n")
}
cat("\nThreshold Call:", x$threshold.call, "\n")
cat("Number Above:", x$nat, "\n")
cat("Proportion Above:", round(x$pat, digits), "\n")
cat("\nEstimates\n")
print.default(format(fitted(x), digits = digits), print.gap = 2,
quote = FALSE)
if(!is.null(x$std.err)) {
cat("\nStandard Errors\n")
print.default(format(x$std.err, digits = digits), print.gap = 2,
quote = FALSE)
}
if(!is.null(x$var.cov)) {
cat("\nAsymptotic Variance Covariance\n")
print.default(format(x$var.cov, digits = digits), print.gap = 2,
quote = FALSE)
}
if(!is.null(x$corr)) {
cat("\nCorrelation\n")
print.default(format(x$corr, digits = digits), print.gap = 2,
quote = FALSE)
}
cat("\nOptimization Information\n")
cat(" Convergence:", x$convergence, "\n")
cat(" Function Evaluations:", x$counts["function"], "\n")
if(!is.na(x$counts["gradient"]))
cat(" Gradient Evaluations:", x$counts["gradient"], "\n")
if(!is.null(x$message)) cat("\nMessage:", x$message, "\n")
cat("\n")
}
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