View source: R/3-inference-functions.R
prob | R Documentation |
Compute (marginal and/or conditional) probabilities of elementary events with respect to the probability encoded in a staged event tree.
prob(object, x, conditional_on = NULL, log = FALSE, na0 = TRUE)
object |
an object of class |
x |
the vector or data.frame of observations. |
conditional_on |
named vector, the conditioning event. |
log |
logical, if |
na0 |
logical, if |
Computes probabilities related to a vector or a data.frame of observations.
Optionally, conditional probabilities can be obtained by specifying
the conditioning event in conditional_on
. This can be done either
with a single named vector or with a data.frame object with the
same number of rows of x
. In the former, the same conditioning
is used for all the computed probabilities (if x
has multiple rows);
while with the latter different conditioning events (but on the same variables)
can be specified for each row of x
.
the probabilities to observe each observation in x
, possibly
conditional on the event(s) in conditional_on
.
data(Titanic) model <- full(Titanic, lambda = 1) samples <- expand.grid(model$tree[c(1, 4)]) pr <- prob(model, samples) ## probabilities sum up to one sum(pr) ## print observations with probabilities print(cbind(samples, probability = pr)) ## compute one probability prob(model, c(Class = "1st", Survived = "Yes")) ## compute conditional probability prob(model, c(Survived = "Yes"), conditional_on = c(Class = "1st")) ## compute conditional probabilities with different conditioning set prob(model, data.frame(Age = rep("Adult", 8)), conditional_on = expand.grid(model$tree[2:1])) ## the above should be the same as summary(model)$stages.info$Age
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