A Likelihood factor models a conditional density function.
The conditioning set is defined as all parent nodes (defined in tmle3_Task
). In the case of a continuous
outcome variable, where a full density isn't needed, this can also model a conditional mean. This is the base class, which
is intended to be abstract. See below for a list of possible likelihood factor classes.
R6Class
object.
LF_base
object
define_lf(LF_base, name, ..., type = "density")
name
character, the name of the factor. Should match a node name in the nodes specified by tmle3_Task$npsem
...
Not currently used.
type
character, either "density", for conditional density or, "mean" for conditional mean
get_density(tmle_task)
Get conditional density values for for the observations in tmle_task
.
tmle_task
: tmle3_Task
to get likelihood values for
get_mean(tmle_task)
Get conditional mean values for for the observations in tmle_task
.
tmle_task
: tmle3_Task
to get likelihood values for
name
character, the name of the factor. Should match a node name in the nodes specified by tmle3_Task$npsem
type
character, either "density", for conditional density or, "mean" for conditional mean
variable_type
variable_type
object, specifying the data type of the outcome variable. Only available after Likelihood training.
values
Possible values of the outcome variable, retrivied from the variable_type
object. Only available after Likelihood training.
Other Likelihood objects:
CF_Likelihood
,
LF_derived
,
LF_emp
,
LF_fit
,
LF_known
,
LF_static
,
LF_targeted
,
Likelihood
,
Targeted_Likelihood
,
define_lf()