distribution
defines probability distributions over observed data, e.g. to set a model likelihood.
distribution(greta_array) <- value distribution(greta_array)
greta_array
a data greta array. For the assignment method it must not already have a probability distribution assigned
value
a greta array with a distribution (see distributions
)
The extract method returns the greta array if it has a distribution, or NULL
if it doesn’t. It has no real use-case, but is included for completeness
# define a model likelihood # observed data and mean parameter to be estimated # (explicitly coerce data to a greta array so we can refer to it later) y <- as_data(rnorm(5, 0, 3)) mu <- uniform(-3, 3) # define the distribution over y (the model likelihood) distribution(y) <- normal(mu, 1) # get the distribution over y distribution(y)