Description Usage Arguments Details Value
View source: R/bootstrap-mixed-effect-em-constrained-polynomial-model.R
EXPIREMENTAL: Bootstrap for fitting polynomial constrained mixed effect model with monotonic mean and (potentially) monotonic random effects. For use with block-random effects (non-crossed), e.g. subject-specific random effects.
1 2 3 | case_bootstrap_constrained_lmm_em(model, N, maxit = 25, tol = 0.01, start,
verbose = F, save_steps = F, check_up = F, verbose_boot = verbose,
parallel = F, cores = 1)
|
model |
model specification made by |
N |
bootstrap size. |
maxit |
maximum number of iterations for each resample. |
tol |
relative tolerance for convergence of parameter values for each resample. |
start |
start values for parameters for each resample. Defaults to NULL. |
verbose |
output current iteration and quasi-log-likelihood value in each resample. |
save_steps |
should each em step be saved and return in a list? |
check_up |
should the algorithm check if the quasi-log-likelihood is improving each iteration? |
verbose_boot |
Output when a bootstrap resample is finished. |
parallel |
Execute in parallel. This will turn off verbose settings. ONLY IMPLEMENTED FOR LINUX/MAC |
cores |
Number of cores to use. |
The interface and default actions of this function are under development and may change without warning. See the mixed effects vignette for usage details. Uses case bootstrapping, where a sample of groups is chosen with replacement and the new estimates are used.
list including estimated mixed effects model(s).
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