#' applies aggregation, followed by transformations to the data
#'
#' @param data.ts a T x N matrix ts object,
#' corresponding to N time series of length T
#' @param transform a character indicating an instantaneous
#' transformation to be applied; current options are
#' "none", "log", and "logistic"
#' @param aggregate a boolean, set to TRUE if all series are to
#' be aggregated into a total
#'
#' @return data.ts: a T x N0 matrix ts object, where N0=1 if
#' aggregate=TRUE, otherwise N0=N
#' @export
#'
sigex.transform <- function(data.ts,transform,aggregate=FALSE)
{
##########################################################################
#
# sigex.transform
# Copyright (C) 2017 Tucker McElroy
#
# 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 3 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, see <https://www.gnu.org/licenses/>.
#
############################################################################
################# Documentation #####################################
#
# Purpose: applies aggregation, followed by transformations to the data
#
# Inputs:
# data.ts: a T x N matrix ts object,
# corresponding to N time series of length T
# transform: a character indicating an instantaneous
# transformation to be applied; current options are
# "none", "log", and "logistic"
# aggregate: a boolean, set to TRUE if all series are to
# be aggregated into a total
# Outputs:
# data.ts: a T x N0 matrix ts object, where N0=1 if
# aggregate=TRUE, otherwise N0=N
#
####################################################################
if(aggregate) {
data <- as.matrix(rowSums(data.ts))
new.names <- "Total"
} else {
data <- data.ts
new.names <- colnames(data.ts)
}
if(transform=="log") data <- log(data)
if(transform=="logistic") data <- log(data) - log(1-data)
if(transform=="none") data <- data
data.ts <- ts(data,start=start(data.ts),frequency=frequency(data.ts),
names=new.names)
return(data.ts)
}
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