Counters are functions that are defined in terms of the change statistics. The counters also contain a hasher that is used internally to check whether an array's support is cached or not (see details).
get_counters(model)# S3 method for DEFM_counters
[(counters, i)
set_counter_info(counter, new_name = "", new_desc = "")
# S3 method for DEFM_counters
length(x)
# S3 method for DEFM_counters
as.list(x, ...)
# S3 method for DEFM_counter
as.list(x, ...)
set_counters_names(x, ...)
# S3 method for DEFM
set_counters_names(x, ...)
# S3 method for DEFM_counters
set_counters_names(x, ...)
The function get_counters returns an external pointer to an object of
class DEFM_counters.
The method [.DEFM_counters returns an individual counter of class
DEFM_counter.
set_counter_info() invisibly returns the modified counter.
The length method for DEFM_counters returns the number of counters
in the vector. This should match the return from nterms_defm().
The as.list methods return a list with the name and description
of the counters.
The function set_counters_names() returns the counters invisibly.
A DEFM model object.
An object of class DEFM_counters.
Integer from 0 to nterms - 1. Counter to get.
An object of class DEFM_counter.
Strings with the new name and new description, respectively. If empty, no side effect.
Either a DEFM_counters or a DEFM_counter object.
Further arguments passed to the method (not used).
If the hash of an array--which are built using each counters' individual hashing functions--matches an existing array, then, the DEFM models reduce computational burden by recycling computations of the normalizing constant. For example, if a model only includes terms (counters) that do not feature individual-level characteristics like gender or age, then most likely all arrays in that model will use the same normalizing constant.
The function set_counter_info() can be used to modify a counter name
and description. This is especially useful when a name is particularly
long.