Learn R Programming

PLNmodels (version 1.3.2)

Poisson Lognormal Models

Description

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 ) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.

Copy Link

Version

Install

install.packages('PLNmodels')

Monthly Downloads

461

Version

1.3.2

License

GPL (>= 3)

Maintainer

Julien Chiquet

Last Published

September 23rd, 2026

Functions in PLNmodels (1.3.2)

PLNfit_diagonal

An R6 Class to represent a PLNfit in a standard, general framework, with diagonal residual covariance

PLNfit_fixedcov

An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariance

Control of PLNPCA fit

An R6 Class to represent a collection of PLNfit

PLNLDAfit_diagonal

An R6 Class to represent a PLNfit in a LDA framework with diagonal covariance

Poisson lognormal model towards Principal Component Analysis

An R6 Class to represent a collection of PLNPCAfit

An R6 Class to represent a PLNfit in a PCA framework

An R6 Class to represent a PLNfit in a standard, general framework

Control of a PLN fit

PLNfit_spherical

An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariance

PLNmixturefamily

An R6 Class to represent a collection of PLNmixturefit

PLNnetwork_param

Control of PLNnetwork fit

An R6 Class to represent a PLNfit with a residual covariance structured by a fixed correlation matrix (e.g. a genetic relationship matrix), motivated by population genetics

Poisson lognormal mixture model

An R6 Class to represent a PLNfit in a mixture framework

Sparse Poisson lognormal model for network inference

PLNmodels-package

PLNmodels: Poisson Lognormal Models

PLNnetworkfamily

An R6 Class to represent a collection of PLNnetworkfits

PLNmixture_param

Control of a PLNmixture fit

An R6 Class to represent a PLNfit in a sparse inverse covariance framework

An R6 Class to represent a ZIPLNfit

ZIPLNfit_sparse

An R6 Class to represent a ZIPLNfit in a standard, general framework, with sparse inverse residual covariance

Control of a ZIPLN fit

ZIPLNnetwork_param

Control of ZIPLNnetwork fit

Zero Inflated Poisson lognormal model

Zero Inflated Sparse Poisson lognormal model for network inference

ZIPLNfit_diagonal

An R6 Class to represent a ZIPLNfit in a standard, general framework, with diagonal residual covariance

An R6 Class to represent a ZIPLNfit in a standard, general framework, with fixed (inverse) residual covariance

ZIPLNfit_spherical

An R6 Class to represent a ZIPLNfit in a standard, general framework, with spherical residual covariance

Extract model coefficients

compute_ZIPLN_starting_point

Helper function for ZIPLN initialization.

coef.PLNmixturefit

Extract model coefficients

Compute offsets from a count data using one of several normalization schemes

compute_PLN_starting_point

Helper function for PLN initialization.

coefficient_path

Extract the regularization path of a PLNnetwork fit

Extract model coefficients

Barents fish data set

Extracts model coefficients from objects returned by PLNLDA()

ZIPLNnetworkfamily

An R6 Class to represent a collection of ZIPLNnetwork

Extract edge selection frequency in bootstrap subsamples

fitted.PLNmixturefit

Extracts model fitted values from objects returned by PLNmixture() and its variants

logLik.ZIPLNfit

Extract log-likelihood of a fitted ZIPLN model

Cow microbiome data set

graphical_lasso

Graphical Lasso

Extract log-likelihood of a fitted PLN model

LDA visualization (individual and/or variable factor map(s)) for a PLNPCAfit object

getBestModel.PLNPCAfamily

Best model extraction from a collection of models

getModel.PLNPCAfamily

Model extraction from a collection of models

plot.PLNPCAfamily

Display the criteria associated with a collection of PLNPCA fits (a PLNPCAfamily)

Predict counts of a new sample

fitted.ZIPLNfit

Extracts model fitted values from objects returned by ZIPLN() and its variants

predict.PLNLDAfit

Predict group of new samples

Extracts model fitted values from objects returned by PLN() and its variants

plot.Networkfamily

Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (either PLNnetworkfamily or ZIPLNnetworkfamily)

Single cell RNA-seq data

Extract variance-covariance of residuals 'Sigma'

Mollusk data set

Calculate Variance-Covariance Matrix for a fitted PLN() model object

Display the criteria associated with a collection of PLN fits (a PLNfamily)

predict.ZIPLNfit

Predict counts of a new sample

predict.PLNmixturefit

Prediction for a PLNmixturefit object

PCA visualization (individual and/or variable factor map(s)) for a PLNPCAfit object

plot.PLNmixturefamily

Display the criteria associated with a collection of PLNmixture fits (a PLNmixturefamily)

standard_error.PLNPCAfit

Component-wise standard errors of B

Trichoptera data set

stability_selection

Compute the stability path by stability selection

Oaks amplicon data set

Extract variance-covariance of residuals 'Sigma'

Predict counts conditionally

sigma.PLNmixturefit

Extract variance-covariance of residuals 'Sigma'

Prepare data for use in PLN models

plot.PLNmixturefit

Mixture visualization of a PLNmixturefit object

plot.ZIPLNfit_sparse

Extract and plot the network (partial correlation, support or inverse covariance) from a ZIPLNfit_sparse object

plot.PLNnetworkfit

Extract and plot the network (partial correlation, support or inverse covariance) from a PLNnetworkfit object

Integrated Classification Likelihood

Poisson lognormal model towards Linear Discriminant Analysis

An R6 Class to virtually represent a collection of network fits

An R6 Class to represent a PLNfit in a LDA framework

Bayesian Information Criterion for a fitted ZIPLN model

Bayesian Information Criterion for a fitted PLN model

Akaike Information Criterion for a fitted ZIPLN model

Poisson lognormal model

Control of a PLNLDA fit

Akaike Information Criterion for a fitted PLN model