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
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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://petolau.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:

data-analysis data-mining data-mining-algorithms data-science representation time-series time-series-analysis time-series-classification time-series-clustering time-series-data-mining time-series-representations cpp

7.26 score 98 stars 124 scripts 585 downloads 1 mentions 51 exports 12 dependencies

Last updated from:1dd7ea8064. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	209
linux-devel-x86_64	NOTE	175
source / vignettes	OK	260
linux-release-arm64	NOTE	191
linux-release-x86_64	NOTE	170
macos-release-arm64	NOTE	181
macos-release-x86_64	NOTE	273
macos-oldrel-arm64	NOTE	175
macos-oldrel-x86_64	NOTE	352
windows-devel	NOTE	139
windows-release	NOTE	131
windows-oldrel	NOTE	135
wasm-release	OK	150

Exports:clipping denorm_atan denorm_boxcox denorm_min_max denorm_yj denorm_z l1Coef lmCoef maape mae mape mase maxC mdae meanC medianC minC mse norm_atan norm_boxcox norm_min_max norm_min_max_list norm_min_max_params norm_yj norm_z norm_z_list norm_z_params repr_dct repr_dft repr_dwt repr_exp repr_feaclip repr_feacliptrend repr_featrend repr_gam repr_list repr_lm repr_matrix repr_paa repr_pip repr_pla repr_sax repr_seas_profile repr_sma repr_windowing rleC rlmCoef rmse smape sumC trending

Dependencies:dtt lattice MASS Matrix MatrixModels mgcv nlme quantreg Rcpp SparseM survival wavelets

TSrepr: Simple extensible framework

Rendered fromTSrepr_extentions.Rmdusingknitr::rmarkdown

Last update: 2020-03-23
Started: 2018-01-01

TSrepr: Time series representations in a use case

Clustering of time series representations | Bibliography

Rendered fromTSrepr_representations_use_case.Rmdusingknitr::rmarkdown

Last update: 2020-03-23
Started: 2017-12-08

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: 2018-11-22
Started: 2017-11-09

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Creates bit-level (clipped representation) from a vector	clipping
Functions for linear regression model coefficients extraction	coefComp l1Coef lmCoef rlmCoef
Arctangent denormalisation	denorm_atan
Two-parameter Box-Cox denormalisation	denorm_boxcox
Min-Max denormalisation	denorm_min_max
Yeo-Johnson denormalisation	denorm_yj
Z-score denormalisation	denorm_z
2 weeks of electricity load data from 50 consumers.	elec_load
Fast statistic functions (helpers)	fast_stat maxC meanC medianC minC sumC
MAAPE	maape
MAE	mae
MAPE	mape
MASE	mase
MdAE	mdae
MSE	mse
Arctangent normalisation	norm_atan
Two-parameter Box-Cox normalisation	norm_boxcox
Min-Max normalisation	norm_min_max
Min-Max normalization list	norm_min_max_list
Min-Max normalisation with parameters	norm_min_max_params
Yeo-Johnson normalisation	norm_yj
Z-score normalisation	norm_z
Z-score normalization list	norm_z_list
Z-score normalisation with parameters	norm_z_params
DCT representation	repr_dct
DFT representation by FFT	repr_dft
DWT representation	repr_dwt
Exponential smoothing seasonal coefficients as representation	repr_exp
FeaClip representation of time series	repr_feaclip
FeaClipTrend representation of time series	repr_feacliptrend
FeaTrend representation of time series	repr_featrend
GAM regression coefficients as representation	repr_gam
Computation of list of representations list of time series with different lengths	repr_list
Regression coefficients from linear model as representation	repr_lm
Computation of matrix of representations from matrix of time series	repr_matrix
PAA - Piecewise Aggregate Approximation	repr_paa
PIP representation	repr_pip
PLA representation	repr_pla
SAX - Symbolic Aggregate Approximation	repr_sax
Mean seasonal profile of time series	repr_seas_profile
Simple Moving Average representation	repr_sma
Windowing of time series	repr_windowing
RLE (Run Length Encoding) written in C++	rleC
RMSE	rmse
sMAPE	smape
Creates bit-level (trending) representation from a vector	trending
TSrepr package	TSrepr