Package: simts 0.2.2
Stéphane Guerrier
simts: Time Series Analysis Tools
A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi:10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.
Authors:
simts_0.2.2.tar.gz
simts_0.2.2.tar.gz(r-4.5-noble)simts_0.2.2.tar.gz(r-4.4-noble)
simts_0.2.2.tgz(r-4.4-emscripten)simts_0.2.2.tgz(r-4.3-emscripten)
simts.pdf |simts.html✨
simts/json (API)
NEWS
| # Install 'simts' in R: |
| install.packages('simts', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/smac-group/simts/issues1 issues
Last updated 2 years agofrom:c5641f497a. Checks:1 OK, 2 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 23 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 23 2025 |
| R-4.4-linux-x86_64 | NOTE | Mar 23 2025 |
Exports:ARAR1ar1_to_gmARIMAARMAARMA11auto_corrbest_modelcheckcombcompare_acfconv.ar1.to.gmconv.gm.to.ar1corr_analysiscreate_imudesc.to.ts.modeldiag_boxpiercediag_ljungboxDRestimateevaluateFGNgen_ar1gen_ar1blocksgen_arimagen_armagen_arma11gen_bigen_drgen_fgngen_generic_sarimagen_gtsgen_ltsgen_lts_cppgen_ma1gen_materngen_meangen_modelgen_nswngen_powerlawgen_qngen_rwgen_sarimagen_sarmagen_singen_wnGMgm_to_ar1gmwmgmwm_master_cppgtsgts_timehasimuis.gtsis.imuis.ltsis.ts.modelis.wholeltsMMAMa_cppMa_cpp_vecMA1make_frameMAPEMATmodel_objdescmodel_process_descmodel_thetanp_boot_sd_medorderModelPLPQNRWRW2dimensionSARIMASARMAselectselect_arselect_arimaselect_armaselect_maSINtheo_acftheo_pacfunitConversionupdate_objvalueWN
Dependencies:backportsbroomclicolorspacecpp11dplyrfansifarvergenericsgluelabelinglifecyclemagrittrmunsellpillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangrobcorscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Citation
To cite package ‘simts’ in publications use:
Guerrier S, Balamuta J, Molinari R, Lee J, Voirol L, Zhang Y (2023). simts: Time Series Analysis Tools. R package version 0.2.2, https://CRAN.R-project.org/package=simts.
Corresponding BibTeX entry:
@Manual{,
title = {simts: Time Series Analysis Tools},
author = {Stéphane Guerrier and James Balamuta and Roberto Molinari
and Justin Lee and Lionel Voirol and Yuming Zhang},
year = {2023},
note = {R package version 0.2.2},
url = {https://CRAN.R-project.org/package=simts},
}
Readme and manuals
simts Overview
simts
The Time Series Tools (simts) R package provides a series of tools to
simulate, plot, estimate, select and forecast different time series
models. Its original purpose was to be a support to the online textbook
“Applied Time Series Analysis with
R” but can obviously be used for time
series analysis in general. More specifically, the package provides
tools with the following features:
- Simulation of time series from SARIMA models to various state-space models that can be expressed as latent time series processes.
- Visualization of time series data with user specifications.
- Specific simulation and visualization tools for latent time series models.
- Easy-to-use functions to estimate and infer on the parameters of time series models through different methods (standard and robust).
- Diagnostic and statistical tools to assess goodness of fit and select the best model for the data.
- Estimating and plotting tools to deliver point forecasts and confidence intervals.
To understand the usage of the simts package, please refer to the
“Vignettes” tab above.
Install Instructions
Installation
The simts package is available on both CRAN and GitHub. The CRAN
version is considered stable while the GitHub version is subject to
modifications/updates which may lead to installation problems or broken
functions. You can install the stable version of the simts package
with:
install.packages("simts")
For users who are interested in having the latest developments, the GitHub version is ideal although more dependencies are required to run a stable version of the package. Most importantly, users must have a (C++) compiler installed on their machine that is compatible with R (e.g. Clang).
# Install dependencies
install.packages(c("RcppArmadillo","devtools","knitr","rmarkdown"))
# Install the package from GitHub without Vignettes/User Guides
devtools::install_github("SMAC-Group/simts")
# Install the package with Vignettes/User Guides
devtools::install_github("SMAC-Group/simts", build_vignettes = TRUE)
The setup to obtain the development version of simts is platform
dependent.
License
The license this source code is released under is the GNU AFFERO GENERAL PUBLIC LICENSE (AGPL) v3.0. Please see the LICENSE file for full text. Otherwise, please consult TLDR Legal or GNU which will provide a synopsis of the restrictions placed upon the code.
