Internal Alternating Optimization Function
fct_alt_optimize(
x,
y,
k,
clust_assign,
lambda,
alt_iter,
anneal_iter,
em_iter,
temp,
mu,
eps,
accept_prob,
sim_N,
verbose
)A final fit of mixedLSR
A matrix of predictors.
A matrix of responses.
The number of groups.
The current clustering assignment.
A vector of penalization parameters.
The maximum number of times to alternate between the classification expectation maximization algorithm and the simulated annealing algorithm.
The maximum number of simulated annealing iterations.
The maximum number of EM iterations.
The initial simulated annealing temperature, temp > 0.
The simulated annealing decrease temperature fraction. Once the best configuration cannot be improved, reduce the temperature to (mu)T, 0 < mu < 1.
The final simulated annealing temperature, eps > 0.
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.
The simulated annealing number of iterations for reaching equilibrium.
A boolean indicating whether to print to screen.