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srlTS  

Sparsity-Ranked Lasso for Time Series
View on CRAN: Click here


Download and install srlTS package within the R console
Install from CRAN:
install.packages("srlTS")

Install from Github:
library("remotes")
install_github("cran/srlTS")

Install by package version:
library("remotes")
install_version("srlTS", "0.1.1")



Attach the package and use:
library("srlTS")
Maintained by
Ryan Andrew Peterson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-14
Latest Update: 2023-12-14
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.
How to cite:
Ryan Andrew Peterson (2023). srlTS: Sparsity-Ranked Lasso for Time Series. R package version 0.1.1, https://cran.r-project.org/web/packages/srlTS. Accessed 28 Feb. 2025.
Previous versions and publish date:
0.1.1 (2023-12-14 09:00)
Other packages that cited srlTS R package
View srlTS citation profile
Other R packages that srlTS depends, imports, suggests or enhances
Complete documentation for srlTS
Functions, R codes and Examples using the srlTS R package
Some associated functions: internal . predict.srlTS . srlTS . uihc_ed_arrivals . 
Some associated R codes: data.R . helpers.R . prediction.R . srlTS.R .  Full srlTS package functions and examples
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