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sparsereg
View on CRAN: Click
here
Download and install sparsereg package within the R console
Install from CRAN:
install.packages("sparsereg")
Install from Github:
library("remotes")
install_github("cran/sparsereg")
Install by package version:
library("remotes")
install_version("sparsereg", "1.2")
Attach the package and use:
library("sparsereg")
Maintained by
Marc Ratkovic
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-07-21
Latest Update: 2016-03-10
Description:
Sparse modeling provides a mean selecting a small number of non-zero effects from a large possible number of candidate effects.This package includes a suite of methods for sparse modeling: estimation via EM or MCMC, approximate confidence intervals with nominal coverage, and diagnostic and summary plots.The method can implement sparse linear regression and sparse probit regression.Beyond regression analyses, applications include subgroup analysis, particularly for conjoint experiments, and panel data. Future versions will include extensions tomodels with truncated outcomes, propensity score, and instrumental variable analysis.
How to cite:
Marc Ratkovic (2015). sparsereg: Sparse Bayesian Models for Regression, Subgroup Analysis, and Panel Data. R package version 1.2, https://cran.r-project.org/web/packages/sparsereg
Other packages that cited sparsereg R package
View sparsereg citation profile
Other R packages that sparsereg depends,
imports, suggests or enhances
Functions, R codes and Examples using
the sparsereg R package
Some associated functions: difference . plot.sparsereg . print.sparsereg . sparsereg-internal . sparsereg-package . sparsereg . summary.sparsereg . violinplot .
Some associated R codes: RcppExports.R . cleandata.R . subgroup.R . updateREs.R . utility.R . Full sparsereg package functions and examples
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