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ppmlasso (version 1.4)

Point Process Models with LASSO-Type Penalties

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.

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Version

Install

install.packages('ppmlasso')

Monthly Downloads

226

Version

1.4

License

GPL-3

Maintainer

Ian Renner

Last Published

January 31st, 2024

Functions in ppmlasso (1.4)

getEnvVar

Extract environmental data to presence locations
print.ppmlasso

Print a fitted regularisation path
predict.ppmlasso

Prediction to new data from a fitted regularisation path
ppmlasso-class

Class "ppmlasso"
pointInteractions

Calculate point interactions for area-interaction models
predict-methods

Methods for function predict
print-methods

Methods for function print
ppmdat

Prepare data for model fitting
ppmlasso-package

PPM-LASSO: Point process models with LASSO-type penalties
ppmlasso-internal

Internal ppmlasso functions
sampleQuad

Generate regular grid of quadrature points with environmental data
ppmlasso

Fit point process models with LASSO penalties
BlueMountains

Blue Mountains eucalypt and environmental data.
plotFit

Plot the predicted intensity of a fitted ppmlasso model
findRes

Choose spatial resolution for analysis
envelope.ppmlasso

Calculates simulation envelopes for goodness-of-fit
plotPath

Plot of the regularisation path of a ppmlasso model
griddify

Ensure that a geo-referenced matrix of environmental grids is rectangular
diagnose-methods

Methods for function diagnose
diagnose.ppmlasso

Create diagnostic plots for a fitted point process model.
envelope-methods

Methods for function envelope