Package: autoTS 0.9.11

autoTS: Automatic Model Selection and Prediction for Univariate Time Series

Offers a set of functions to easily make predictions for univariate time series. 'autoTS' is a wrapper of existing functions of the 'forecast' and 'prophet' packages, harmonising their outputs in tidy dataframes and using default values for each. The core function getBestModel() allows the user to effortlessly benchmark seven algorithms along with a bagged estimator to identify which one performs the best for a given time series.

Authors:Vivien Roussez

autoTS_0.9.11.tar.gz
autoTS_0.9.11.zip(r-4.7)autoTS_0.9.11.zip(r-4.6)autoTS_0.9.11.zip(r-4.5)
autoTS_0.9.11.tgz(r-4.6-any)autoTS_0.9.11.tgz(r-4.5-any)
autoTS_0.9.11.tar.gz(r-4.7-any)autoTS_0.9.11.tar.gz(r-4.6-any)
autoTS_0.9.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
autoTS/json (API)

# Install 'autoTS' in R:

install.packages('autoTS', repos = c('https://vivienroussez.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vivienroussez/autots/issues

On CRAN:

4.78 score 10 stars 12 scripts 208 downloads 15 exports 111 dependencies

Last updated from:b457c02215. Checks:1 ERROR, 2 OK, 6 NOTE. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	ERROR	163
source / vignettes	OK	238
linux-release-x86_64	NOTE	160
macos-release-arm64	NOTE	157
macos-oldrel-arm64	NOTE	178
windows-devel	NOTE	100
windows-release	NOTE	126
windows-oldrel	NOTE	93
wasm-release	OK	162

Exports:complete.ts getBestModel getFrequency my.bats my.ets my.mae my.predictions my.prophet my.rmse my.sarima my.shortterm my.stlm my.tbats prepare.ts runUserInterface

Dependencies:abind askpass backports base64enc BH bslib cachem callr checkmate cli colorspace commonmark cpp11 crosstalk curl data.table desc digest distributional dplyr dygraphs evaluate extraDistr farver fastmap fontawesome forecast fracdiff fs generics ggplot2 glue gridExtra gtable highr htmltools htmlwidgets httpuv httr inline isoband jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle lmtest loo lubridate magrittr matrixStats memoise mime nlme nnet numDeriv openssl otel pillar pkgbuild pkgconfig plotly posterior processx promises prophet ps purrr QuickJSR R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel RcppRoll rlang rmarkdown rstan rstantools S7 sass scales shiny shinycssloaders sourcetools StanHeaders stringi stringr sys tensorA tibble tidyr tidyselect timechange timeDate tinytex urca utf8 vctrs viridisLite withr xfun xtable xts yaml zoo

Introduction to autoTS

Vivien Roussez

Rendered fromautoTS_vignette.Rmdusingknitr::rmarkdownon Jun 03 2026.

Last update: 2020-06-05
Started: 2020-05-07

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Creates additional dates and values when NA where removed and the TS is not complete	complete.ts
Determine best algorithm	getBestModel
Determines the decimal frequency of a time series from a character string	getFrequency
Fit BATS algorithm and make the prediction	my.bats
Fit ETS algorithm and make the prediction	my.ets
Custom (internal) function for MAE	my.mae
Make predictions with selected algorithms	my.predictions
Fit prophet algorithm and make the prediction	my.prophet
Custom (internal) function for RMSE	my.rmse
Fit SARIMA algorithm and make the prediction	my.sarima
Fit short term algorithm and make the prediction	my.shortterm
Fit STLM algorithm and make the prediction	my.stlm
Fit TBATS algorithm and make the prediction	my.tbats
Format 2 vectors in a proper object usable by all algorithms	prepare.ts
Demo graphical user interface	runUserInterface