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