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")
namecharacter, the name of the factor. Should match a node name in the nodes specified by tmle3_Task$npsem
...Not currently used.
typecharacter, either "density", for conditional density or, "mean" for conditional mean
get_density(tmle_task)Get conditional density values for for the observations in tmle_task.
tmle_task: tmle3_Task to get likelihood values for
get_mean(tmle_task)Get conditional mean values for for the observations in tmle_task.
tmle_task: tmle3_Task to get likelihood values for
namecharacter, the name of the factor. Should match a node name in the nodes specified by tmle3_Task$npsem
typecharacter, either "density", for conditional density or, "mean" for conditional mean
variable_typevariable_type object, specifying the data type of the outcome variable. Only available after Likelihood training.
valuesPossible 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()