ZIPLN_param.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ZIPLN.R
\name{ZIPLN_param}
\alias{ZIPLN_param}
\title{Control of a ZIPLN fit}
\usage{
ZIPLN_param(
  backend = c("nlopt"),
  trace = 1,
  covariance = c("full", "diagonal", "spherical", "fixed", "sparse"),
  Omega = NULL,
  penalty = 0,
  penalize_diagonal = TRUE,
  penalty_weights = NULL,
  config_post = list(),
  config_optim = list(),
  inception = NULL
)
}
\arguments{
\item{backend}{optimization back used, either "nlopt" or "torch". Default is "nlopt"}

\item{trace}{a integer for verbosity.}

\item{covariance}{character setting the model for the covariance matrix. Either "full", "diagonal", "spherical" or "fixed". Default is "full".}

\item{Omega}{precision matrix of the latent variables. Inverse of Sigma. Must be specified if \code{covariance} is "fixed"}

\item{penalty}{a user-defined penalty to sparsify the residual covariance. Defaults to 0 (no sparsity).}

\item{penalize_diagonal}{boolean: should the diagonal terms be penalized in the graphical-Lasso? Default is \code{TRUE}}

\item{penalty_weights}{either a single or a list of p x p matrix of weights (default: all weights equal to 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.}

\item{config_post}{a list for controlling the post-treatments (optional bootstrap, jackknife, R2, etc.). See details}

\item{config_optim}{a list for controlling the optimizer (either "nlopt" or "torch" backend). See details}

\item{inception}{Set up the parameters initialization: by default, the model is initialized with a multivariate linear model applied on
log-transformed data, and with the same formula as the one provided by the user. However, the user can provide a PLNfit (typically obtained from a previous fit),
which sometimes speeds up the inference.}
}
\value{
list of parameters used during the fit and post-processing steps
}
\description{
Helper to define list of parameters to control the PLN fit. All arguments have defaults.
}
\details{
See \code{\link[=PLN_param]{PLN_param()}} and \code{\link[=PLNnetwork_param]{PLNnetwork_param()}} for a full description of the generic optimization parameters. Like \code{\link[=PLNnetwork_param]{PLNnetwork_param()}}, ZIPLN_param() has two parameters controlling the optimization due the inner-outer loop structure of the optimizer:
\itemize{
\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than \code{ftol_out} multiplied by the absolute value of the parameter. Default is 1e-6
\item "maxit_out" outer solver stops when the number of iteration exceeds \code{maxit_out}. Default is 100
and one additional parameter controlling the form of the variational approximation of the zero inflation:
\item "approx_ZI" either uses an exact or approximated conditional distribution for the zero inflation. Default is FALSE
}
}