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specs  

Single-Equation Penalized Error-Correction Selector (SPECS)
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("specs", "1.0.1")



Attach the package and use:
library("specs")
Maintained by
Etienne Wijler
[Scholar Profile | Author Map]
First Published: 2020-07-06
Latest Update: 2024-02-29
Description:
Implementation of SPECS, your favourite Single-Equation Penalized Error-Correction Selector developed in Smeekes and Wijler (2021) <doi:10.1016/j.jeconom.2020.07.021>. SPECS provides a fully automated estimation procedure for large and potentially (co)integrated datasets. The dataset in levels is converted to a conditional error-correction model, either by the user or by means of the functions included in this package, and various specialised forms of penalized regression can be applied to the model. Automated options for initializing and selecting a sequence of penalties, as well as the construction of penalty weights via an initial estimator, are available. Moreover, the user may choose from a number of pre-specified deterministic configurations to further simplify the model building process.
How to cite:
Etienne Wijler (2020). specs: Single-Equation Penalized Error-Correction Selector (SPECS). R package version 1.0.1, https://cran.r-project.org/web/packages/specs. Accessed 28 Feb. 2025.
Previous versions and publish date:
0.1.0 (2020-07-06 15:40), 0.1.1 (2020-07-17 14:20)
Other packages that cited specs R package
View specs citation profile
Other R packages that specs depends, imports, suggests or enhances
Complete documentation for specs
Functions, R codes and Examples using the specs R package
Some associated functions: Unempl_GT . specs . specs_opt . specs_tr . specs_tr_opt . 
Some associated R codes: RcppExports.R . Unempl_GT.R . specs-package.R . specs.R .  Full specs package functions and examples
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