ProjectedGD {rMultiNet}

Title

Description

Title

Usage

ProjectedGD(
  Ini_list,
  cmax = 1,
  eta_outer = 0.001,
  tmax_outer = 10,
  p_type = "logit",
  rd = "Non",
  show = TRUE,
  sgma = 1,
  sample_size = 500
)

Arguments

Ini_list

the output of function InitializationLSM

cmax

the upper limits for adding the coefficient constraint

eta_outer

the learning rate in gradient descent

tmax_outer

the number of iterations in gradient descent

p_type

the type of link function (‘logit’, ‘probit’ or ‘poisson’ )

rd

whether to use stochastic sampling (‘rand’ or ‘Non’ )

show

if print the ietation process

sgma

the link function parameter

sample_size

the size of sampling

Value

the embedding results of nodes and layers

Examples

gen_list = GenerateMMLSM(200,3,5,2,d=NULL)
Ini_list = InitializationLSM(gen_list,200,3,2)