Evaluate the probability density of a probability distribution

For discrete distributions, the probability mass function. pmf() is an alias.

Usage

pdf(d, x, drop = TRUE, ...)

log_pdf(d, x, ...)

pmf(d, x, ...)

Arguments

d

A probability distribution object such as those created by a call to Bernoulli(), Beta(), or Binomial().

x

A vector of elements whose probabilities you would like to determine given the distribution d.

drop

logical. Should the result be simplified to a vector if possible?

...

Unused. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

Value

Probabilities corresponding to the vector x.

Examples

X <- Normal()

pdf(X, c(1, 2, 3, 4, 5))
#> [1] 2.419707e-01 5.399097e-02 4.431848e-03 1.338302e-04 1.486720e-06
pmf(X, c(1, 2, 3, 4, 5))
#> [1] 2.419707e-01 5.399097e-02 4.431848e-03 1.338302e-04 1.486720e-06

log_pdf(X, c(1, 2, 3, 4, 5))
#> [1]  -1.418939  -2.918939  -5.418939  -8.918939 -13.418939