Package: fastTS Type: Package Title: Fast Time Series Modeling for Seasonal Series with Exogenous Variables Version: 1.0.3 Authors@R: person("Ryan Andrew", "Peterson", email = "ryan-peterson@uiowa.edu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-4650-5798")) Description: An implementation of sparsity-ranked lasso and related methods for time series data. This methodology is especially useful for large time series with exogenous features and/or complex seasonality. Originally described in Peterson and Cavanaugh (2022) in the context of variable selection with interactions and/or polynomials, ranked sparsity is a philosophy with methods useful for variable selection in the presence of prior informational asymmetry. This situation exists for time series data with complex seasonality, as shown in Peterson and Cavanaugh (2024) , which also describes this package in greater detail. The sparsity-ranked penalization methods for time series implemented in 'fastTS' can fit large/complex/high-frequency time series quickly, even with a high-dimensional exogenous feature set. The method is considerably faster than its competitors, while often producing more accurate predictions. Also included is a long hourly series of arrivals into the University of Iowa Emergency Department with concurrent local temperature. Suggests: covr, kableExtra, knitr, magrittr, rmarkdown, testthat (>= 3.0.0), tibble Imports: dplyr, methods, ncvreg, RcppRoll, rlang, yardstick Depends: R (>= 3.5) License: GPL (>= 3) Encoding: UTF-8 LazyData: true RoxygenNote: 7.3.3 Config/testthat/edition: 3 VignetteBuilder: knitr URL: https://petersonr.github.io/fastTS/, https://github.com/petersonR/fastTS/ BugReports: https://github.com/petersonR/fastTS/issues Date: 2025-11-29 Repository: https://petersonr.r-universe.dev Date/Publication: 2025-11-29 21:55:08 UTC RemoteUrl: https://github.com/petersonr/fastts RemoteRef: HEAD RemoteSha: 9cd20ae6dc2f220b59f5e7b203f1eb53a2c35e0a NeedsCompilation: no Packaged: 2026-05-28 07:52:40 UTC; root Author: Ryan Andrew Peterson [aut, cre, cph] (ORCID: ) Maintainer: Ryan Andrew Peterson