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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
################################################################################
# FUNCTION: DESCRIPTION:
# assetsArrange Rearranges the columns in a deta set of assets
# FUNCTION: DESCRIPTION:
# pcaArrange Returns PCA correlation ordered column names
# hclustArrange Returns hierarchical clustered column names
# abcArrange Returns sorted column names
# orderArrange Returns ordered column names
# sampleArrange Returns sampled column names
# statsArrange Returns statistically rearranged column names
################################################################################
assetsArrange <-
function(x, method = c("pca", "hclust", "abc"), ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns ordered column names of a time Series
# Arguments:
# x - S4 object of class 'timeSeries'
# FUNCTION:
# Settings:
method <- match.arg(method)
FUN <- paste(method, "Arrange", sep = "")
arrange <- match.fun(FUN)
# Return Value:
arrange(x, ...)
}
# ------------------------------------------------------------------------------
pcaArrange <-
function(x, robust = FALSE, ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns PCA correlation ordered column names
# Arguments:
# x - S4 object of class 'timeSeries'
# Notes:
# Requires package "robustbase".
# FUNCTION:
# Order:
if (robust) {
x.cor <- robustbase::covMcd(as.matrix(x), cor = TRUE, ...)$cor
} else {
x.cor <- cor(as.matrix(x), ...)
}
x.eigen <- eigen(x.cor)$vectors[,1:2]
e1 <- x.eigen[, 1]
e2 <- x.eigen[, 2]
Order <- order(ifelse(e1 > 0, atan(e2/e1), atan(e2/e1)+pi))
ans <- colnames(as.matrix(x))[Order]
# Return Value:
ans
}
# ------------------------------------------------------------------------------
hclustArrange <-
function(x, method = c("euclidean", "complete"), ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns hierarchical clustered column names
# Arguments:
# x - S4 object of class 'timeSeries'
# ...
# method - the agglomeration method to be used. This should
# be (an unambiguous abbreviation of) one of "ward", "single",
# "complete", "average", "mcquitty", "median" or "centroid".
# FUNCTION:
# Order:
Order <- hclust(
dist(t(as.matrix(x)),
method = method[1]),
method = method[2], ...)$order
ans <- colnames(as.matrix(x))[Order]
# Return Value:
ans
}
# ------------------------------------------------------------------------------
abcArrange <-
function(x, ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns sorted column names of a time Series
# Arguments:
# x - S4 object of class 'timeSeries'
# FUNCTION:
# Sort:
ans <- sort(colnames(as.matrix(x)), ...)
# Return Value:
ans
}
# ------------------------------------------------------------------------------
orderArrange <-
function(x, ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns ordered column names of a time Series
# Arguments:
# x - S4 object of class 'timeSeries'
# FUNCTION:
# Order:
ans <- order(colnames(as.matrix(x)), ...)
# Return Value:
ans
}
# ------------------------------------------------------------------------------
sampleArrange <-
function(x, ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns sampled column names of a time Series
# Arguments:
# x - S4 object of class 'timeSeries'
# FUNCTION:
# Sample:
ans <- sample(colnames(as.matrix(x)), ...)
# Return Value:
ans
}
# ------------------------------------------------------------------------------
statsArrange <-
function(x, FUN = colMeans, ...)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns statistically rearranged column names
# Arguments:
# x - S4 object of class 'timeSeries'
# Note:
# Example of function Candidates:
# colStats calculates column statistics,
# colSums calculates column sums,
# colMeans calculates column means,
# colSds calculates column standard deviations,
# colVars calculates column variances,
# colSkewness calculates column skewness,
# colKurtosis calculates column kurtosis,
# colMaxs calculates maximum values in each column,
# colMins calculates minimum values in each column,
# colProds computes product of all values in each column,
# colQuantiles computes quantiles of each column.
# FUNCTION:
# Apply colStats Function:
fun <- match.fun(FUN)
Sort <- sort(fun(x, ...))
Order <- names(Sort)
ans <- colnames(as.matrix(x)[, Order])
attr(ans, "control") <- Sort
# Return Value:
ans
}
################################################################################
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