delayed_optimization: Optimize the parameters of a Negative Binomial regression...

Description Usage Arguments Value

View source: R/newFit.R

Description

The parameters of the model given as argument are optimized by penalized maximum likelihood on the count matrix given as argument.

Usage

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delayed_optimization(
  Y,
  cluster,
  children,
  model,
  max_iter,
  stop_epsilon,
  n_gene_disp,
  n_cell_par,
  n_gene_par,
  commondispersion,
  verbose
)

Arguments

cluster

The PSOCK cluster

children

Number of child process

model

newmodel item

max_iter

maximum number of iterations

stop_epsilon

stopping criterion, when the relative gain in likelihood is below epsilon

n_gene_disp

number of genes used in mini-batch dispersion estimation approach(default NULL > all genes are used)

n_cell_par

number of cells used in mini-batch cell's related parameters estimation approach(default NULL > all cells are used)

n_gene_par

number of genes used in mini-batch gene's related parameters estimation approach(default NULL > all genes are used)

commondispersion

Whether or not a single dispersion for all features is estimated (default TRUE).

verbose

print information (default FALSE)

Value

An object of class newmodel similar to the one given as argument with modified parameters alpha, beta, gamma, W.


NewWave documentation built on Dec. 26, 2020, 6 p.m.