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
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autoTS.pdf |autoTS.html✨
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:

15 exports 9 stars 1.40 score 119 dependencies 12 scripts 271 downloads

Last updated 4 years agofrom:b457c02215. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 11 2024
R-4.5-win	NOTE	Sep 11 2024
R-4.5-linux	NOTE	Sep 11 2024
R-4.4-win	NOTE	Sep 11 2024
R-4.4-mac	NOTE	Sep 11 2024
R-4.3-win	NOTE	Sep 11 2024
R-4.3-mac	NOTE	Sep 11 2024

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 crayon crosstalk curl data.table desc digest distributional dplyr dygraphs evaluate extraDistr fansi 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 MASS Matrix matrixStats memoise mgcv mime munsell nlme nnet numDeriv openssl pillar pkgbuild pkgconfig plotly posterior processx promises prophet ps purrr quadprog quantmod QuickJSR R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel RcppRoll rlang rmarkdown rstan rstantools sass scales shiny shinycssloaders sourcetools StanHeaders stringi stringr sys tensorA tibble tidyr tidyselect timechange timeDate tinytex tseries TTR urca utf8 vctrs viridisLite withr xfun xtable xts yaml zoo

Introduction to autoTS

Vivien Roussez

Rendered fromautoTS_vignette.Rmdusingknitr::rmarkdownon Sep 11 2024.

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