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-4.7)nnlasso_0.3.zip(r-4.6)nnlasso_0.3.zip(r-4.5)
nnlasso_0.3.tgz(r-4.6-any)nnlasso_0.3.tgz(r-4.5-any)
nnlasso_0.3.tar.gz(r-4.7-any)nnlasso_0.3.tar.gz(r-4.6-any)
nnlasso_0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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 from:601e3cf0cc. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 95 | ||
| source / vignettes | OK | 150 | ||
| linux-release-x86_64 | OK | 95 | ||
| macos-release-arm64 | OK | 67 | ||
| macos-oldrel-arm64 | OK | 86 | ||
| windows-devel | OK | 73 | ||
| windows-release | OK | 70 | ||
| windows-oldrel | OK | 64 | ||
| wasm-release | OK | 83 |
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:
