fct_alt_optimize {mixedLSR}R Documentation

Internal Alternating Optimization Function

Description

Internal Alternating Optimization Function

Usage

fct_alt_optimize(
  x,
  y,
  k,
  clust_assign,
  lambda,
  alt_iter,
  anneal_iter,
  em_iter,
  temp,
  mu,
  eps,
  accept_prob,
  sim_N,
  verbose
)

Arguments

x

A matrix of predictors.

y

A matrix of responses.

k

The number of groups.

clust_assign

The current clustering assignment.

lambda

A vector of penalization parameters.

alt_iter

The maximum number of times to alternate between the classification expectation maximization algorithm and the simulated annealing algorithm.

anneal_iter

The maximum number of simulated annealing iterations.

em_iter

The maximum number of EM iterations.

temp

The initial simulated annealing temperature, temp > 0.

mu

The simulated annealing decrease temperature fraction. Once the best configuration cannot be improved, reduce the temperature to (mu)T, 0 < mu < 1.

eps

The final simulated annealing temperature, eps > 0.

accept_prob

The simulated annealing probability of accepting a new assignment 0 < accept_prob < 1. When closer to 1, trial assignments will only be small perturbation of the current assignment. When closer to 0, trial assignments are closer to random.

sim_N

The simulated annealing number of iterations for reaching equilibrium.

verbose

A boolean indicating whether to print to screen.

Value

A final fit of mixedLSR


[Package mixedLSR version 0.1.0 Index]