Package: nnlasso 0.3

nnlasso: Non-Negative Lasso and Elastic Net Penalized Generalized Linear Models

Estimates of coefficients of lasso penalized linear regression and generalized linear models subject to non-negativity constraints on the parameters using multiplicative iterative algorithm. Entire regularization path for a sequence of lambda values can be obtained. Functions are available for creating plots of regularization path, cross validation and estimating coefficients at a given lambda value. There is also provision for obtaining standard error of coefficient estimates.

Authors:Baidya Nath Mandal <[email protected]> and Jun Ma <[email protected]>

nnlasso_0.3.tar.gz
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nnlasso_0.3.tgz(r-4.4-any)nnlasso_0.3.tgz(r-4.3-any)
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nnlasso_0.3.tgz(r-4.4-emscripten)nnlasso_0.3.tgz(r-4.3-emscripten)
nnlasso.pdf |nnlasso.html
nnlasso/json (API)

# Install 'nnlasso' in R:
install.packages('nnlasso', repos = c('https://doer0.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • car - The car data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

20 exports 1 stars 1.08 score 0 dependencies 1 dependents 2 mentions 8 scripts 151 downloads

Last updated 9 years agofrom:601e3cf0cc. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-winOKAug 20 2024
R-4.5-linuxOKAug 20 2024
R-4.4-winOKAug 20 2024
R-4.4-macOKAug 20 2024
R-4.3-winOKAug 20 2024
R-4.3-macOKAug 20 2024

Exports:barscoef.nnlassocv.nnlassocv.nnlasso.binomialcv.nnlasso.normalcv.nnlasso.poissonfoldkfoldmsefun.binomialmsefun.normalmsefun.poissonnnlassonnlasso.binomialnnlasso.binomial.lambdannlasso.normalnnlasso.normal.lambdannlasso.poissonnnlasso.poisson.lambdaplot.nnlassopredict.nnlasso

Dependencies: