Helper to define list of parameters to control the PLNmixture fit. All arguments have defaults.

  backend = "nlopt",
  trace = 1,
  covariance = "spherical",
  init_cl = "kmeans",
  smoothing = "both",
  config_optim = list(),
  config_post = list(),
  inception = NULL



optimization back used, either "nlopt" or "torch". Default is "nlopt"


a integer for verbosity.


character setting the model for the covariance matrices of the mixture components. Either "full", "diagonal" or "spherical". Default is "spherical".


The initial clustering to apply. Either, 'kmeans', CAH' or a user defined clustering given as a list of clusterings, the size of which is equal to the number of clusters considered. Default is 'kmeans'.


The smoothing to apply. Either, 'none', forward', 'backward' or 'both'. Default is 'both'.


a list for controlling the optimizer (either "nlopt" or "torch" backend). See details


a list for controlling the post-treatments (optional bootstrap, jackknife, R2, etc.).


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.


list of parameters configuring the fit.


See PLN_param() for a full description of the generic optimization parameters. PLNmixture_param() also has additional parameters controlling the optimization due the inner-outer loop structure of the optimizer:

  • "ftol_out" outer solver stops when an optimization step changes the objective function by less than xtol multiplied by the absolute value of the parameter. Default is 1e-6

  • "maxit_out" outer solver stops when the number of iteration exceeds maxit_out. Default is 50

  • "it_smoothing" number of the iterations of the smoothing procedure. Default is 1.

See also