Run TRICEP/BICEP for generalized linear models.
1 2 3 4 5 6 7 8 9 10 | TRICEP_glm(beta_test, X, y, F_reparam = NULL, s_hat_reparam = NULL,
prox_fun = NULL, detect_outlier = F, q = NULL, reuse_delta = F,
prox_fun_arg = list(), family = c("gaussian", "binomial", "poisson"),
wts_init = NULL, beta_opt_type = c("closed_form", "LBFGS"),
vary_penalty = c("RB", "RB2", "none"), RB_mu = 10, RB_tau = 2,
RB2_ksi = 2, outer_eps = 1e-08, outer_rel_eps = 1e-04, dual_step = 2,
outer_maxit = 1000, wts_beta_rep = 1, outer_tol_type = c("primal_dual",
"fval", "primal"), outlier_loop_arg = optim_outlier_control(),
mirror_arg = optim_mirror_control(line_search = T), lbfgs_arg = list(gtol
= 0.1, invisible = 1), prox_optim_arg = optim_prox_control(), verbose = F)
|
beta_test |
a vector of candidate test values. |
X |
a design matrix with observations in rows and variables in columns. |
y |
a vector of the responses. |
F_reparam |
the |
s_hat_reparam |
the |
prox_fun |
a proximal operator. This should be an |
detect_outlier |
a boolean indicating whether an REL update should be run to detect outliers. |
q |
the number of detected outliers (only valid if |
reuse_delta |
use the last estimate of |
prox_fun_arg |
a list of arguments passed to |
family |
the family for the canonical link function. |
wts_init |
an initial guess for the weights vector. Default is |
beta_opt_type |
the optimization type for the |
vary_penalty |
a string specifying the type of penalty variation. |
RB_mu |
the |
RB_tau |
the |
RB2_ksi |
the |
outer_eps |
absolute tolerance required for outer loop convergence. |
outer_rel_eps |
relative tolerance required for outer loop convergence. |
dual_step |
initial penalty parameter. |
outer_maxit |
maximum number of outer loop iterations. |
wts_beta_rep |
the number of repetitions of the block coordinate descent update within each outer loop iteration. |
outer_tol_type |
the type of tolerance check for the outer loop. |
outlier_loop_arg |
control arguments passed to the |
mirror_arg |
control arguments passed to the mirror descent optimization; see |
lbfgs_arg |
a list of control arguments passed to |
prox_optim_arg |
a list of control arguments passed to the proximal gradient descent update for |
verbose |
a boolean to allow console output. |
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