Toplevel fitting functionsSet of functions to fit variants of the Poisson lognormal model 


PLNmodels 

Poisson lognormal model 

Poisson lognormal model towards Linear Discriminant Analysis 

Poisson lognormal model towards Principal Component Analysis 

Poisson lognormal model towards sparse network inference 

Poisson lognormal mixture model 

Poisson lognormal fitDescription of the PLNfit object and methods for its manipulation. Any PLN variant in the package inherits from this class (PLNPCAfit, PLNnetworkfit, PLNLDAfit). 

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

Extract model coefficients 

Calculate VarianceCovariance Matrix for a fitted 

Extract variancecovariance of residuals 'Sigma' 

Predict counts of a new sample 

Predict counts conditionally 

Extracts model fitted values from objects returned by 

Componentwise standard errors of Theta 

Fisher information matrix for Theta 

Linear discriminant analysis via a Poisson lognormal fitDescription of the PLNLDAfit object and methods for its manipulation. 

An R6 Class to represent a PLNfit in a LDA framework 

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

Predict group of new samples 

Extracts model coefficients from objects returned by 

Poisson Lognormal PCA fitDescription of the PLNPCAfit and PLNPCAfamily objects and methods for their manipulation. 

An R6 Class to represent a PLNfit in a PCA framework 

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

An R6 Class to represent a collection of PLNPCAfit 

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

Best model extraction from a collection of models 

Model extraction from a collection of models 

Mixture of Poisson Lognormal fitsDescription of the PLNmixturefit and PLNmixturefamily objects and methods for their manipulation. 

An R6 Class to represent a PLNfit in a mixture framework 

Mixture visualization of a 

An R6 Class to represent a collection of PLNmixturefit 

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

Extract model coefficients 

Prediction for a 

Extract variancecovariance of residuals 'Sigma' 

Extracts model fitted values from objects returned by 

Best model extraction from a collection of models 

Model extraction from a collection of models 

Sparse Poisson lognormal fit and networkDescription of the PLNnetworkfit and PLNnetworkfamily objects and methods for their manipulation. 

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

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

An R6 Class to represent a collection of PLNnetworkfit 

Display various outputs (goodnessoffit criteria, robustness, diagnostic) associated with a collection of PLNnetwork fits (a 

Best model extraction from a collection of models 

Model extraction from a collection of models 

Extract the regularization path of a PLNnetwork fit 

Compute the stability path by stability selection 

Extract edge selection frequency in bootstrap subsamples 

Other functions and objects 

Prepare data for use in PLN models 

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

An R6 Class to represent a collection of PLNfit 

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

PLN RNG 

Data sets 

Trichoptera data set 

Mollusk data set 

Oaks amplicon data set 