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# The distances in TSclust are calculated by means of the following wrapper functions. The functions of the TSclust package are directly used.
# Autocorrelation based similarity
ACFDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.ACF(x, y, ...))},
error=function(e) {print(e); NA})
}
# Partial autocorrelation based similarity
PACFDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.PACF(x, y, ...))},
error=function(e) {print(e); NA})
}
# Dissimilarity Based on LPC Cepstral Coefficients
ARLPCCepsDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.AR.LPC.CEPS(x, y, ...))},
error=function(e) {print(e); NA})
}
# Model-based Dissimilarity Proposed by Maharaj (1996, 2000)
ARMahDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
diss.AR.MAH(x, y, ...)},
error=function(e) {print(e); NA})
}
ARMahStatisticDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.AR.MAH(x, y, ...)$statistic)},
error=function(e) {print(e); NA})
}
ARMahPvalueDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.AR.MAH(x, y, ...)$p_value)},
error=function(e) {print(e); NA})
}
# Model-based Dissimilarity Measure Proposed by Piccolo (1990)
ARPicDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.AR.PIC(x, y, ...))},
error=function(e) {print(e); NA})
}
# Compression-based Dissimilarity measure
CDMDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.CDM(x, y, ...))},
error=function(e) {print(e); NA})
}
# Complexity-Invariant Distance Measure For Time Series
CIDDistance <- function(x, y) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.CID(x, y))},
error=function(e) {print(e); NA})
}
# Correlation-based Dissimilarity
CorDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.COR(x, y, ...))},
error=function(e) {print(e); NA})
}
# Dissimilarity Index Combining Temporal Correlation and Raw Values
# Behaviors
CortDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.CORT(x, y, ...))},
error=function(e) {print(e); NA})
}
# Integrated Periodogram Based Dissimilarity
IntPerDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.INT.PER(x, y, ...))},
error=function(e) {print(e); NA})
}
# Periodogram Based Dissimilarity
PerDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.PER(x, y, ...))},
error=function(e) {print(e); NA})
}
# Symbolic Aggregate Aproximation related functions
MindistSaxDistance <- function(x, y, w, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.MINDIST.SAX(x, y, w, ...))},
error=function(e) {print(e); NA})
}
# Normalized Compression Distance
NCDDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.NCD(x, y, ...))},
error=function(e) {print(e); NA})
}
# Dissimilarity Measure Based on Nonparametric Forecast
PredDistance <- function(x, y, h, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.PRED(x, y, h, ...)$L1dist)},
error=function(e) {print(e); NA})
}
# Dissimilarity based on the Generalized Likelihood Ratio Test
SpecGLKDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss(rbind(x,y), "SPEC.GLK", ...))},
error=function(e) {print(e); NA})
}
# Dissimilarity Based on the Integrated Squared Difference between the
# Log-Spectra
SpecISDDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.SPEC.ISD(x, y, ...))},
error=function(e) {print(e); NA})
}
# General Spectral Dissimilarity Measure Using Local-Linear Estima-
# tion of the Log-Spectra
SpecLLRDistance <- function(x, y, ...) {
# If there is an error, NA is returned and the error message
# is printed. This enables executing in batch mode, without stops.
tryCatch ({
as.numeric(diss.SPEC.LLR(x, y, ...))},
error=function(e) {print(e); NA})
}
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