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NVCSSL  

Nonparametric Varying Coefficient Spike-and-Slab Lasso
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("NVCSSL", "2.0")



Attach the package and use:
library("NVCSSL")
Maintained by
Ray Bai
[Scholar Profile | Author Map]
First Published: 2020-06-09
Latest Update: 2020-06-09
Description:
Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) . Functions to fit frequentist penalized varying coefficients are also provided, with the option of employing the group lasso penalty of Yuan and Lin (2006) , the group minimax concave penalty (MCP) of Breheny and Huang , or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) .
How to cite:
Ray Bai (2020). NVCSSL: Nonparametric Varying Coefficient Spike-and-Slab Lasso. R package version 2.0, https://cran.r-project.org/web/packages/NVCSSL. Accessed 30 Apr. 2025.
Previous versions and publish date:
1.0 (2020-06-09 11:40)
Other packages that cited NVCSSL R package
View NVCSSL citation profile
Other R packages that NVCSSL depends, imports, suggests or enhances
Complete documentation for NVCSSL
Functions, R codes and Examples using the NVCSSL R package
Some associated functions: NVC_SSL . NVC_frequentist . SimulatedData . predict_NVC . robustified_NVC_SSL . yeast . 
Some associated R codes: NVC_SSL.R . NVC_frequentist.R . helper_functions.R . predict_NVC.R . robustified_NVC_SSL.R .  Full NVCSSL package functions and examples
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