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:Ian Renner

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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'))

Peer review:

Datasets:

On CRAN:

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

14 exports 2 stars 0.36 score 23 dependencies 14 scripts 334 downloads

Last updated 8 months agofrom:780c839708. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 31 2024
R-4.5-winNOTEAug 31 2024
R-4.5-linuxNOTEAug 31 2024
R-4.4-winOKAug 31 2024
R-4.4-macOKAug 31 2024
R-4.3-winOKAug 31 2024
R-4.3-macOKAug 31 2024

Exports:diagnosediagnose.ppmlassoenvelope.ppmlassofindResgetEnvVargriddifyplotFitplotPathpointInteractionsppmdatppmlassopredict.ppmlassoprint.ppmlassosampleQuad

Dependencies:abinddata.tabledeldirgoftestlatticeMatrixmgcvnlmeplyrpolyclipRcpprpartspatstatspatstat.dataspatstat.explorespatstat.geomspatstat.linnetspatstat.modelspatstat.randomspatstat.sparsespatstat.univarspatstat.utilstensor