nbfar (version 0.1)

nbfar_control: Control parameters for NBFAR and NBRRR

Description

Default value for a list of control parameters that are used to estimate the parameters of negative binomial co-sparse factor regression (NBFAR) and negative binomial reduced rank regression (NBRRR).

Usage

nbfar_control(
  maxit = 5000,
  epsilon = 1e-07,
  elnetAlpha = 0.95,
  gamma0 = 1,
  spU = 0.5,
  spV = 0.5,
  lamMaxFac = 1,
  lamMinFac = 1e-06,
  initmaxit = 10000,
  initepsilon = 1e-08,
  objI = 0
)

Arguments

maxit

maximum iteration for each sequential steps

epsilon

tolerance value required for convergence of inner loop in GCURE

elnetAlpha

elastic net penalty parameter

gamma0

power parameter for generating the adaptive weights

spU

maximum proportion of nonzero elements in each column of U

spV

maximum proportion of nonzero elements in each column of V

lamMaxFac

a multiplier of the computed maximum value (lambda_max) of the tuning parameter

lamMinFac

a multiplier to determine lambda_min as a fraction of lambda_max

initmaxit

maximum iteration for minimizing the objective function while computing the initial estimates of the model parameter

initepsilon

tolerance value required for the convergence of the objective function while computing the initial estimates of the model parameter

objI

1 or 0 to indicate that the convergence will be on the basis of objective function or not

Value

a list of controlling parameter.

References

Mishra, A., M<U+00FC>ller, C. (2022) Negative binomial factor regression models with application to microbiome data analysis. https://doi.org/10.1101/2021.11.29.470304

Examples

# NOT RUN {
control <- nbfar_control()
# }