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.

LF_base

## Format

R6Class object.

## Value

LF_base object

## Constructor

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$npsem ... Not currently used. type character, either "density", for conditional density or, "mean" for conditional mean ## Methods get_density(tmle_task) Get conditional density values for for the observations in tmle_task. • tmle_task: tmle3_Task to get likelihood values for get_mean(tmle_task) Get conditional mean values for for the observations in tmle_task. • tmle_task: tmle3_Task to get likelihood values for ## Fields name character, the name of the factor. Should match a node name in the nodes specified by tmle3_Task$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_emp, LF_fit, LF_known, LF_static, Likelihood, Targeted_Likelihood, define_lf