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# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library 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 Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA 02111-1307 USA
################################################################################
# S3-METHODS: PRINT METHOD:
# show.fREG Prints results from a regression model fit
################################################################################
setMethod(f = "show", signature(object = "fREG"), definition =
function(object)
{
# A function implemented by Diethelm Wuertz
# Description:
# Print method for Regression Modelling, an object of class "fREG"
# FUNCTION:
# Title:
cat("\nTitle:\n ")
cat(as.character(object@title), "\n")
# Call:
# cat("\nCall:\n")
# cat(paste(deparse(object@call), sep = "\n", collapse = "\n"),
# "\n", sep = "")
# Formula:
cat("\nFormula:\n ")
# cat(as.character(object@formula), "\n")
print(object@formula)
# Family:
if (object@family[1] != "" && object@family[2] != "") {
cat("\nFamily:\n ")
cat(as.character(object@family[1:2]), "\n") }
# Digits:
digits = max(4, getOption("digits") - 4)
# Model Parameters:
cat("\nModel Parameters:\n")
# Regression Model LM / RLM:
if (object@method == "lm" | object@method == "rlm") {
print.default(format(object@fit$coef, digits = digits),
print.gap = 2, quote = FALSE)
}
# Regression Model GLM:
if (object@method == "glm") {
if (length(object@fit$coef)) {
# if (is.character(co = object@fit$contrasts))
co <- object@fit$contrasts
if (is.character(co))
cat(" [contrasts: ", apply(cbind(names(co), co),
1, paste, collapse = "="), "]")
# cat(":\n")
print.default(format(object@fit$coefficients,
digits = digits), print.gap = 2, quote = FALSE)
} else {
cat("No coefficients\n\n")
}
}
# Regression Model GAM:
if (object@method == "gam" | object@method == "am") {
print.default(format(object@fit$coef, digits = digits),
print.gap = 2, quote = FALSE)
}
# Regression Model PPR:
if (object@method == "ppr") {
cat("-- Projection Direction Vectors --\n")
print(object@fit$alpha)
cat("-- Coefficients of Ridge Terms --\n")
print(object@fit$beta)
}
# Regression Model POLYMARS:
if (object@method == "polymars") {
print(object@fit$coef)
}
# Regression Model NNET:
if (object@method == "nnet") {
cat(" a ",object@fit$n[1], "-", object@fit$n[2], "-",
object@fit$n[3], " network", " with ",
length(object@fit$wts), " weights\n", sep="")
cat(" options were -")
tconn = diff(object@fit$nconn)
if (tconn[length(tconn)] > object@fit$n[2]+1)
cat(" skip-layer connections ")
if (object@fit$nunits > object@fit$nsunits &&
!object@fit$softmax)
cat(" linear output units ")
if (object@fit$entropy)
cat(" entropy fitting ")
if (object@fit$softmax)
cat(" softmax modelling ")
if (object@fit$decay[1] > 0)
cat(" decay=", object@fit$decay[1], sep="")
cat("\n")
Weights = object@fit$wts
print(Weights)
}
# Residual Variance:
# cat("\nResidual Variance:\n", var(object@fit$residuals))
cat("\n")
# Return Value:
invisible()
})
###############################################################################
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