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ppmlasso
View on CRAN: Click
here
Download and install ppmlasso package within the R console
Install from CRAN:
install.packages("ppmlasso")
Install from Github:
library("remotes")
install_github("cran/ppmlasso") Install by package version:
library("remotes")
install_version("ppmlasso", "1.5") Attach the package and use:
library("ppmlasso")
Maintained by
Ian Renner
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-10-15
Latest Update: 2025-09-03
Description:
Toolkit for fitting point process models with sequences of LASSO penalties ("regularisation paths"), as described in Renner, I.W. and Warton, D.I. (2013) . 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.
How to cite:
Ian Renner (2013). ppmlasso: Point Process Models with LASSO-Type Penalties. R package version 1.5, https://cran.r-project.org/web/packages/ppmlasso. Accessed 29 Aug. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for ppmlasso
Functions, R codes and Examples using
the ppmlasso R package
Some associated functions: BlueMountains . diagnose-methods . diagnose.ppmlasso . envelope-methods . envelope.ppmlasso . findRes . getEnvVar . griddify . plotFit . plotPath . pointInteractions . ppmdat . ppmlasso-class . ppmlasso-internal . ppmlasso-package . ppmlasso . predict-methods . predict.ppmlasso . print-methods . print.ppmlasso . sampleQuad .
Some associated R codes: ppmlasso_functions.R . Full ppmlasso package functions and examples
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