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This model driver for flexmix implements model-based clustering of PKB distributions using neural network in the M-step.
FLXMRpkb( formula = . ~ ., EPOCHS = 100, LR = 0.1, max_iter = 200, adam_iter = 5, free_iter = adam_iter, line_search_fn = "strong_wolfe" )
Returns an object of class FLXMC.
FLXMC
A formula.
The number of epochs in the M-step estimation (default: 100).
The learning rate used in the M-step estimation (default: 0.1).
The maximum number of iterations of the LBFGS optimizer (default: 200).
The number of iteration for which the adam optimizer is used before the algorithm switches to L-BFGS (default: 5).
The number of initial iterations for which the model in M-step is fully reseted (default: adam_iter).
The method used for line search in LBFGS (default: "strong_wolfe").
# \donttest{ if(torch::torch_is_installed()){ mix <- rbind(rpkb(30, 0.95, c(1, 0, 0)), rpkb(30, 0.9, c(-1, 0, 0))) m1 <- flexmix::flexmix(mix ~ 1, k = 2, model = FLXMRpkb()) } # }
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