Package: srlTS
Type: Package
Title: Sparsity-Ranked Lasso for Time Series
Version: 0.1.1
Authors@R: person("Ryan Andrew", "Peterson", 
                  email = "ryan.a.peterson@cuanschutz.edu", 
                  role = c("aut", "cre", "cph"),
                  comment = c(ORCID = "0000-0002-4650-5798"))
Description: An implementation of sparsity-ranked lasso 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) <doi:10.1007/s10182-021-00431-7> 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 
    (2023+) <doi:10.48550/arXiv.2211.01492>, which also describes this package
    in greater detail. The Sparsity-Ranked Lasso (SRL) for Time Series  
    implemented in 'srlTS' can fit large/complex/high-frequency time series
    quickly, even with a high-dimensional exogenous feature set. The SRL 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)
Imports: dplyr, methods, ncvreg, RcppRoll, rlang, yardstick
Depends: R (>= 3.5)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://petersonr.github.io/srlTS/,
        https://github.com/petersonR/srlTS/
BugReports: https://github.com/petersonR/srlTS/issues
Date: 2023-12-13
NeedsCompilation: no
Packaged: 2023-12-13 22:46:23 UTC; ryanpeterson
Author: Ryan Andrew Peterson [aut, cre, cph]
    (<https://orcid.org/0000-0002-4650-5798>)
Maintainer: Ryan Andrew Peterson <ryan.a.peterson@cuanschutz.edu>
Repository: CRAN
Date/Publication: 2023-12-14 08:00:02 UTC
Built: R 4.4.2; ; 2024-12-08 03:15:29 UTC; windows
