Package: TSrepr 1.1.0

Peter Laurinec

TSrepr: Time Series Representations

Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also various normalisation methods (min-max, z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.

Authors:Peter Laurinec [aut, cre]

TSrepr_1.1.0.tar.gz
TSrepr_1.1.0.zip(r-4.7-x86_64)TSrepr_1.1.0.zip(r-4.7-arm64)TSrepr_1.1.0.zip(r-4.6-x86_64)TSrepr_1.1.0.zip(r-4.6-arm64)TSrepr_1.1.0.zip(r-4.5-x86_64)
TSrepr_1.1.0.tgz(r-4.6-x86_64)TSrepr_1.1.0.tgz(r-4.6-arm64)TSrepr_1.1.0.tgz(r-4.5-x86_64)TSrepr_1.1.0.tgz(r-4.5-arm64)
TSrepr_1.1.0.tar.gz(r-4.7-arm64)TSrepr_1.1.0.tar.gz(r-4.7-x86_64)TSrepr_1.1.0.tar.gz(r-4.6-arm64)TSrepr_1.1.0.tar.gz(r-4.6-x86_64)
TSrepr_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TSrepr/json (API)

# Install 'TSrepr' in R:
install.packages('TSrepr', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/petolau/tsrepr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • elec_load - 2 weeks of electricity load data from 50 consumers.

On CRAN:

Conda:

archivedpackagesr-universecpp

4.27 score 5 stars 124 scripts 436 downloads 1 mentions 51 exports 12 dependencies

Last updated from:40b8e1ec78 (on package/TSrepr). Checks:13 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE130
linux-devel-x86_64NOTE169
source / vignettesOK265
linux-release-arm64NOTE130
linux-release-x86_64NOTE187
macos-release-arm64NOTE152
macos-release-x86_64NOTE295
macos-oldrel-arm64NOTE127
macos-oldrel-x86_64NOTE266
windows-devel-arm64NOTE253
windows-devel-x86_64NOTE198
windows-release-arm64NOTE226
windows-release-x86_64NOTE131
windows-oldrel-x86_64NOTE176
wasm-releaseOK94

Exports:clippingdenorm_atandenorm_boxcoxdenorm_min_maxdenorm_yjdenorm_zl1CoeflmCoefmaapemaemapemasemaxCmdaemeanCmedianCminCmsenorm_atannorm_boxcoxnorm_min_maxnorm_min_max_listnorm_min_max_paramsnorm_yjnorm_znorm_z_listnorm_z_paramsrepr_dctrepr_dftrepr_dwtrepr_exprepr_feacliprepr_feacliptrendrepr_featrendrepr_gamrepr_listrepr_lmrepr_matrixrepr_paarepr_piprepr_plarepr_saxrepr_seas_profilerepr_smarepr_windowingrleCrlmCoefrmsesmapesumCtrending

Dependencies:dttlatticeMASSMatrixMatrixModelsmgcvnlmequantregRcppSparseMsurvivalwavelets

TSrepr: Simple extensible framework
Rendered fromTSrepr_extentions.Rmdusingknitr::rmarkdown

Last update: 2026-10-12
Started: 2026-10-12

TSrepr: Time series representations in R
Implemented methods and functions | Usage of the TSrepr package | Bibliography
Rendered fromTSrepr_representations_of_time_series.Rmdusingknitr::rmarkdown

Last update: 2026-10-12
Started: 2026-10-12

TSrepr: Time series representations in a use case
Clustering of time series representations | Bibliography
Rendered fromTSrepr_representations_use_case.Rmdusingknitr::rmarkdown

Last update: 2026-10-12
Started: 2026-10-12

Readme and manuals

Help Manual

Help pageTopics
Creates bit-level (clipped representation) from a vectorclipping
Functions for linear regression model coefficients extractioncoefComp l1Coef lmCoef rlmCoef
Arctangent denormalisationdenorm_atan
Two-parameter Box-Cox denormalisationdenorm_boxcox
Min-Max denormalisationdenorm_min_max
Yeo-Johnson denormalisationdenorm_yj
Z-score denormalisationdenorm_z
2 weeks of electricity load data from 50 consumers.elec_load
Fast statistic functions (helpers)fast_stat maxC meanC medianC minC sumC
MAAPEmaape
MAEmae
MAPEmape
MASEmase
MdAEmdae
MSEmse
Arctangent normalisationnorm_atan
Two-parameter Box-Cox normalisationnorm_boxcox
Min-Max normalisationnorm_min_max
Min-Max normalization listnorm_min_max_list
Min-Max normalisation with parametersnorm_min_max_params
Yeo-Johnson normalisationnorm_yj
Z-score normalisationnorm_z
Z-score normalization listnorm_z_list
Z-score normalisation with parametersnorm_z_params
DCT representationrepr_dct
DFT representation by FFTrepr_dft
DWT representationrepr_dwt
Exponential smoothing seasonal coefficients as representationrepr_exp
FeaClip representation of time seriesrepr_feaclip
FeaClipTrend representation of time seriesrepr_feacliptrend
FeaTrend representation of time seriesrepr_featrend
GAM regression coefficients as representationrepr_gam
Computation of list of representations list of time series with different lengthsrepr_list
Regression coefficients from linear model as representationrepr_lm
Computation of matrix of representations from matrix of time seriesrepr_matrix
PAA - Piecewise Aggregate Approximationrepr_paa
PIP representationrepr_pip
PLA representationrepr_pla
SAX - Symbolic Aggregate Approximationrepr_sax
Mean seasonal profile of time seriesrepr_seas_profile
Simple Moving Average representationrepr_sma
Windowing of time seriesrepr_windowing
RLE (Run Length Encoding) written in C++rleC
RMSErmse
sMAPEsmape
Creates bit-level (trending) representation from a vectortrending
TSrepr packageTSrepr