This package is considered a duplicate. The official version of this package is found at:https://pln-team.r-universe.dev/PLNmodels

Package: PLNmodels 1.2.2

Julien Chiquet

PLNmodels: Poisson Lognormal Models

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) 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.

Authors:Julien Chiquet [aut, cre], Mahendra Mariadassou [aut], Stéphane Robin [aut], François Gindraud [aut], Julie Aubert [ctb], Bastien Batardière [ctb], Giovanni Poggiato [ctb], Cole Trapnell [ctb], Maddy Duran [ctb]

PLNmodels_1.2.2.tar.gz
PLNmodels_1.2.2.tar.gz(r-4.7-arm64)PLNmodels_1.2.2.tar.gz(r-4.7-x86_64)PLNmodels_1.2.2.tar.gz(r-4.6-arm64)PLNmodels_1.2.2.tar.gz(r-4.6-x86_64)
PLNmodels_1.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PLNmodels/json (API)
NEWS

# Install 'PLNmodels' in R:

install.packages('PLNmodels', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pln-team/plnmodels/issues

Pkgdown/docs site:https://pln-team.github.io

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

barents - Barents fish data set
mollusk - Mollusk data set
oaks - Oaks amplicon data set
scRNA - Single cell RNA-seq data
trichoptera - Trichoptera data set

On CRAN:

openblas cpp

4.23 score 245 scripts 377 downloads 26 exports 57 dependencies

Last updated from:a5d7121bfe. Checks:6 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	398
linux-devel-x86_64	OK	425
source / vignettes	OK	484
linux-release-arm64	OK	423
linux-release-x86_64	OK	433
wasm-release	OK	200

Exports:%>%coefficient_path compute_offset compute_PLN_starting_point extract_probs getBestModel getModel PLN PLN_param PLNLDA PLNLDA_param PLNmixture PLNmixture_param PLNnetwork PLNnetwork_param PLNPCA PLNPCA_param predict_cond prepare_data rPLN stability_selection standard_error ZIPLN ZIPLN_param ZIPLNnetwork ZIPLNnetwork_param

Dependencies:bit bit64 callr cli codetools coro corrplot cpp11 desc digest dplyr farver future future.apply generics ggplot2 glassoFast globals glue gridExtra gtable igraph isoband jsonlite labeling lattice lifecycle listenv magrittr MASS Matrix nloptr parallelly pillar pkgconfig processx ps pscl purrr R6 RColorBrewer Rcpp RcppArmadillo rlang S7 safetensors scales stringi stringr tibble tidyr tidyselect torch utf8 vctrs viridisLite withr

Analyzing multivariate count data with the Poisson log-normal model

PLN team

Rendered fromPLN.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-08-24
Started: 2019-05-17

Clustering of multivariate count data with PLN-mixture

PLN team

Rendered fromPLNmixture.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-01-06
Started: 2021-03-16

Description of the Trichoptera data set

PLN team

Rendered fromTrichoptera.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-01-06
Started: 2019-05-17

Dimension reduction of multivariate count data with PLN-PCA

PLN team

Rendered fromPLNPCA.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-01-06
Started: 2019-05-17

Data importation in PLNmodels

PLN team

Rendered fromImport_data.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2024-01-09
Started: 2019-05-17

Sparse structure estimation for multivariate count data with PLN-network

PLN team

Rendered fromPLNnetwork.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-01-06
Started: 2019-05-17

Supervized classification of multivariate count table with the Poisson discriminant Analysis

PLN team

Rendered fromPLNLDA.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2023-01-06
Started: 2019-05-17

Help page	Topics
Barents fish data set	barents
Extract model coefficients	coef.PLNfit
Extracts model coefficients from objects returned by 'PLNLDA()'	coef.PLNLDAfit
Extract model coefficients	coef.PLNmixturefit
Extract model coefficients	coef.ZIPLNfit
Extract the regularization path of a PLNnetwork fit	coefficient_path
Compute offsets from a count data using one of several normalization schemes	compute_offset
Helper function for PLN initialization.	compute_PLN_starting_point
Extract edge selection frequency in bootstrap subsamples	extract_probs
Extracts model fitted values from objects returned by 'PLN()' and its variants	fitted.PLNfit
Extracts model fitted values from objects returned by 'PLNmixture()' and its variants	fitted.PLNmixturefit
Extracts model fitted values from objects returned by 'ZIPLN()' and its variants	fitted.ZIPLNfit
Best model extraction from a collection of models	getBestModel getBestModel.Networkfamily getBestModel.PLNmixturefamily getBestModel.PLNnetworkfamily getBestModel.PLNPCAfamily getBestModel.ZIPLNnetworkfamily
Model extraction from a collection of models	getModel getModel.Networkfamily getModel.PLNmixturefamily getModel.PLNnetworkfamily getModel.PLNPCAfamily getModel.ZIPLNnetworkfamily
Mollusk data set	mollusk
An R6 Class to virtually represent a collection of network fits	Networkfamily
Oaks amplicon data set	oaks
Poisson lognormal model	PLN
Control of a PLN fit	PLN_param
An R6 Class to represent a collection of PLNfit	PLNfamily
An R6 Class to represent a PLNfit in a standard, general framework	PLNfit
An R6 Class to represent a PLNfit in a standard, general framework, with diagonal residual covariance	PLNfit_diagonal PLNLDAfit_spherical
An R6 Class to represent a PLNfit in a standard, general framework, with fixed (inverse) residual covariance	PLNfit_fixedcov
An R6 Class to represent a PLNfit in a standard, general framework, with spherical residual covariance	PLNfit_spherical
Poisson lognormal model towards Linear Discriminant Analysis	PLNLDA
Control of a PLNLDA fit	PLNLDA_param
An R6 Class to represent a PLNfit in a LDA framework	PLNLDAfit
An R6 Class to represent a PLNfit in a LDA framework with diagonal covariance	PLNLDAfit_diagonal
Poisson lognormal mixture model	PLNmixture
Control of a PLNmixture fit	PLNmixture_param
An R6 Class to represent a collection of PLNmixturefit	PLNmixturefamily
An R6 Class to represent a PLNfit in a mixture framework	PLNmixturefit
Sparse Poisson lognormal model for network inference	PLNnetwork
Control of PLNnetwork fit	PLNnetwork_param
An R6 Class to represent a collection of 'PLNnetworkfit's	PLNnetworkfamily
An R6 Class to represent a PLNfit in a sparse inverse covariance framework	PLNnetworkfit
Poisson lognormal model towards Principal Component Analysis	PLNPCA
Control of PLNPCA fit	PLNPCA_param
An R6 Class to represent a collection of PLNPCAfit	PLNPCAfamily
An R6 Class to represent a PLNfit in a PCA framework	PLNPCAfit
Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (either 'PLNnetworkfamily' or 'ZIPLNnetworkfamily')	plot.Networkfamily plot.PLNnetworkfamily plot.ZIPLNnetworkfamily
Display the criteria associated with a collection of PLN fits (a PLNfamily)	plot.PLNfamily
LDA visualization (individual and/or variable factor map(s)) for a 'PLNPCAfit' object	plot.PLNLDAfit
Display the criteria associated with a collection of PLNmixture fits (a PLNmixturefamily)	plot.PLNmixturefamily
Mixture visualization of a 'PLNmixturefit' object	plot.PLNmixturefit
Extract and plot the network (partial correlation, support or inverse covariance) from a 'PLNnetworkfit' object	plot.PLNnetworkfit
Display the criteria associated with a collection of PLNPCA fits (a PLNPCAfamily)	plot.PLNPCAfamily
PCA visualization (individual and/or variable factor map(s)) for a 'PLNPCAfit' object	plot.PLNPCAfit
Extract and plot the network (partial correlation, support or inverse covariance) from a 'ZIPLNfit_sparse' object	plot.ZIPLNfit_sparse
Predict counts conditionally	predict_cond predict_cond.PLNfit
Predict counts of a new sample	predict.PLNfit
Predict group of new samples	predict.PLNLDAfit
Prediction for a 'PLNmixturefit' object	predict.PLNmixturefit
Predict counts of a new sample	predict.ZIPLNfit
Prepare data for use in PLN models	prepare_data
PLN RNG	rPLN
Single cell RNA-seq data	scRNA
Extract variance-covariance of residuals 'Sigma'	sigma.PLNfit
Extract variance-covariance of residuals 'Sigma'	sigma.PLNmixturefit
Extract variance-covariance of residuals 'Sigma'	sigma.ZIPLNfit
Compute the stability path by stability selection	stability_selection
Component-wise standard errors of B	standard_error standard_error.PLNfit standard_error.PLNfit_fixedcov standard_error.PLNmixturefit standard_error.PLNnetworkfit standard_error.PLNPCAfit
Trichoptera data set	trichoptera
Calculate Variance-Covariance Matrix for a fitted 'PLN()' model object	vcov.PLNfit
Zero Inflated Poisson lognormal model	ZIPLN
Control of a ZIPLN fit	ZIPLN_param
An R6 Class to represent a ZIPLNfit	ZIPLNfit
An R6 Class to represent a ZIPLNfit in a standard, general framework, with diagonal residual covariance	ZIPLNfit_diagonal
An R6 Class to represent a ZIPLNfit in a standard, general framework, with fixed (inverse) residual covariance	ZIPLNfit_fixed
An R6 Class to represent a ZIPLNfit in a standard, general framework, with sparse inverse residual covariance	ZIPLNfit_sparse
An R6 Class to represent a ZIPLNfit in a standard, general framework, with spherical residual covariance	ZIPLNfit_spherical
Zero Inflated Sparse Poisson lognormal model for network inference	ZIPLNnetwork
Control of ZIPLNnetwork fit	ZIPLNnetwork_param
An R6 Class to represent a collection of ZIPLNnetwork	ZIPLNnetworkfamily

Package: PLNmodels 1.2.2

PLNmodels: Poisson Lognormal Models

Analyzing multivariate count data with the Poisson log-normal model

Clustering of multivariate count data with PLN-mixture

Description of the Trichoptera data set

Dimension reduction of multivariate count data with PLN-PCA

Data importation in PLNmodels

Sparse structure estimation for multivariate count data with PLN-network

Supervized classification of multivariate count table with the Poisson discriminant Analysis

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)