codacy-badger/plnmodels

A collection of Poisson lognormal models for multivariate count data analysis

PLNmodels: Poisson lognormal models

The Poisson lognormal model and variants can be used for a variety of multivariate problems when count data are at play (including PCA for count data and network inference). This package implements an efficient algorithm to fit such models accompanied with a set of functions for vizualisation and diagnostic.

Installation

System Requirements

Installation requires a system version of nlopt 2.4-2

• On Debian or Ubuntu use libnlopt-dev:

sudo apt-get install libnlopt-dev

• On Fedora or similar use NLopt-devel:

sudo yum install NLopt-devel

• With Mac OS X, install nlopt via homebrew

brew install nlopt

• On Windows, the package now builds and installs correctly, by including static libraries on compilation. However, I just test it with appveyor so I have never run PLNmodels on Windows: any feedbacks welcomed!

R Package installation

## w/o vignettes
devtools::install_github("jchiquet/PLNmodels")
devtools::install_github("jchiquet/PLNmodels", build_vignettes = TRUE)

Usage and main fitting functions

The package comes with a ecological data to present the functionality

library(PLNmodels)
data(trichoptera)

The main fitting functions work with the usual R formula notations, with mutivariate responses on the left hand side. You probably want to start by one of them. Check the corresponding vignette and documentation page.

Unpenalized Poisson lognormal model (aka PLN)

myPLN <- PLN(Abundance ~ 1, data = trichoptera)

Rank Contraint Poisson lognormal for Poisson Principal Component Analysis (ala PLNPCA)

myPCA <- PLNPCA(Abundance ~ 1, data = trichoptera, ranks = 1:8)

Poisson lognormal discriminant analysis (aka PLNLDA)

myLDA <- PLNLDA(Abundance ~ 1, grouping = trichoptera$Group, data = trichoptera)

Sparse Poisson lognormal model for sparse covariance inference for counts (aka PLNnetwork)

myPLNnetwork <- PLNnetwork(Abundance ~ 1, data = trichoptera)

References

Please cite our work using the following references:

• J. Chiquet, M. Mariadassou and S. Robin: Variational inference for probabilistic Poisson PCA, the Annals of Applied Statistics, to appear. link

• J. Chiquet, M. Mariadassou and S. Robin: Variational inference for sparse network reconstruction from count data, arXiv preprint, 2018. link