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:
nnlasso_0.3.tar.gz
nnlasso_0.3.zip(r-4.5)nnlasso_0.3.zip(r-4.4)nnlasso_0.3.zip(r-4.3)
nnlasso_0.3.tgz(r-4.4-any)nnlasso_0.3.tgz(r-4.3-any)
nnlasso_0.3.tar.gz(r-4.5-noble)nnlasso_0.3.tar.gz(r-4.4-noble)
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')) |
- car - The car data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 years agofrom:601e3cf0cc. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 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: