Package: ppmlasso 1.4
ppmlasso: Point Process Models with LASSO-Type Penalties
Toolkit for fitting point process models with sequences of LASSO penalties ("regularisation paths"), as described in Renner, I.W. and Warton, D.I. (2013) <doi:10.1111/j.1541-0420.2012.01824.x>. Regularisation paths of Poisson point process models or area-interaction models can be fitted with LASSO, adaptive LASSO or elastic net penalties. A number of criteria are available to judge the bias-variance tradeoff.
Authors:
ppmlasso_1.4.tar.gz
ppmlasso_1.4.zip(r-4.5)ppmlasso_1.4.zip(r-4.4)ppmlasso_1.4.zip(r-4.3)
ppmlasso_1.4.tgz(r-4.4-any)ppmlasso_1.4.tgz(r-4.3-any)
ppmlasso_1.4.tar.gz(r-4.5-noble)ppmlasso_1.4.tar.gz(r-4.4-noble)
ppmlasso_1.4.tgz(r-4.4-emscripten)ppmlasso_1.4.tgz(r-4.3-emscripten)
ppmlasso.pdf |ppmlasso.html✨
ppmlasso/json (API)
NEWS
# Install 'ppmlasso' in R: |
install.packages('ppmlasso', repos = c('https://iwrenner.r-universe.dev', 'https://cloud.r-project.org')) |
- BlueMountains - Blue Mountains eucalypt and environmental data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:780c839708. Checks:OK: 5 NOTE: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 19 2024 |
R-4.5-win | NOTE | Nov 19 2024 |
R-4.5-linux | NOTE | Nov 19 2024 |
R-4.4-win | OK | Nov 19 2024 |
R-4.4-mac | OK | Nov 19 2024 |
R-4.3-win | OK | Nov 19 2024 |
R-4.3-mac | OK | Nov 19 2024 |
Exports:diagnosediagnose.ppmlassoenvelope.ppmlassofindResgetEnvVargriddifyplotFitplotPathpointInteractionsppmdatppmlassopredict.ppmlassoprint.ppmlassosampleQuad
Dependencies:abinddata.tabledeldirgoftestlatticeMatrixmgcvnlmeplyrpolyclipRcpprpartspatstatspatstat.dataspatstat.explorespatstat.geomspatstat.linnetspatstat.modelspatstat.randomspatstat.sparsespatstat.univarspatstat.utilstensor