sparsereg
Sparse Bayesian Models for Regression, Subgroup Analysis, and Panel Data
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 to models with truncated outcomes, propensity score, and instrumental variable analysis.
- Version1.2
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release03/10/2016
Documentation
Team
Marc Ratkovic
Dustin Tingley
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Last 30 days
This package has been downloaded 147 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,976 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jun 18, 2024 with 37 downloads.
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Dependencies
- Depends2 packages
- Imports8 packages
- Linking To2 packages