Fit the multivariate Poisson lognormal model with a variational algorithm. Use the (g)lm syntax for model specification (covariates, offsets, weights).

PLN(formula, data, subset, weights, control = PLN_param())

## Arguments

formula

an object of class "formula": a symbolic description of the model to be fitted.

data

an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which PLN is called.

subset

an optional vector specifying a subset of observations to be used in the fitting process.

weights

an optional vector of observation weights to be used in the fitting process.

control

a list-like structure for controlling the optimization, with default generated by PLN_param(). See the associated documentation for details.

## Value

an R6 object with class PLNfit

The class PLNfit and the configuration function PLN_param()

## Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
myPLN <- PLN(Abundance ~ 1, data = trichoptera)
#>
#>  Initialization...
#>  Adjusting a full covariance PLN model with nlopt optimizer
#>  Post-treatments...
#>  DONE!