First public release.
meow() runs a full CAT administration simulation from three swappable
modules: a data loader, an item selection function, and a parameter update
function.R and an
integer administration matrix admin; person and item parameters are kept as
data frames so users can add arbitrary parameters.
(pers, item, R, admin, adj_mat, ...) and
return an updated admin matrix with newly administered cells marked
non-zero.(pers, item, R, admin, ...) and return a
list with updated pers and item data frames.data_existing(), data_simple_1pl()), item selectors
(select_sequential(), select_random(), select_max_info(),
select_restrict_rate(), select_max_dist(),
select_max_dist_enhanced()), and parameter updaters
(update_theta_mle(), update_maths_garden(), update_prowise_learn()).meow_long() converts the matrix state to a long
(id, item, resp) data frame, meow_administered() returns a logical mask of
administered items, and construct_adj_mat() builds the item co-exposure
matrix.meow() accepts a keep_adj_mats argument; set it to FALSE to retain only
the final adjacency matrix and save memory on large or long simulations.