Package: NVCSSL 2.0

Ray Bai

NVCSSL: Nonparametric Varying Coefficient Spike-and-Slab Lasso

Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) <arxiv:1907.06477>. Functions to fit frequentist penalized varying coefficients are also provided, with the option of employing the group lasso penalty of Yuan and Lin (2006) <doi:10.1111/j.1467-9868.2005.00532.x>, the group minimax concave penalty (MCP) of Breheny and Huang <doi:10.1007/s11222-013-9424-2>, or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) <doi:10.1007/s11222-013-9424-2>.

Authors:Ray Bai

NVCSSL_2.0.tar.gz
NVCSSL_2.0.tar.gz(r-4.5-noble)NVCSSL_2.0.tar.gz(r-4.4-noble)
NVCSSL_2.0.tgz(r-4.4-emscripten)NVCSSL_2.0.tgz(r-4.3-emscripten)
NVCSSL.pdf |NVCSSL.html✨
NVCSSL/json (API)

Peer review:

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3 exports 0.00 score 76 dependencies 204 downloads

Last updated 1 years agofrom:cdae39c1d9. Checks:OK: 2. Indexed: yes.

Exports:NVC_frequentistNVC_predictNVC_SSL

Dependencies:abindbackportsbootbroomcarcarDataclicodacolorspacecorrplotcowplotcpp11daeDerivdoBydplyrfansifarvergenericsggplot2ggpubrggrepelggsciggsignifGIGrvggluegridExtragrpreggtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttryCatchLogutf8vctrsviridisLitewithr