variable() creates greta arrays representing unknown parameters, to be learned during model fitting. These parameters are not associated with a probability distribution. To create a variable greta array following a specific probability distribution, see distributions.

variable(lower = -Inf, upper = Inf, dim = 1)

Arguments

lower, upper

scalar values giving optional limits to variables. These must be specified as numerics, they cannot be greta arrays (though see details for a workaround). They can be set to -Inf (lower) or Inf (upper), though lower must always be less than upper.

dim

the dimensions of the greta array to be returned, either a scalar or a vector of positive integers. See details.

Details

lower and upper must be fixed, they cannot be greta arrays. This ensures these values can always be transformed to a continuous scale to run the samplers efficiently. However, a variable parameter with dynamic limits can always be created by first defining a variable constrained between 0 and 1, and then transforming it to the required scale. See below for an example.

Examples

# NOT RUN {
# a scalar variable
a <- variable()

# a positive length-three variable
b <- variable(lower = 0, dim = 3)

# a 2x2x2 variable bounded between 0 and 1
c <- variable(lower = 0, upper = 1, dim = c(2, 2, 2))

# create a variable, with lower and upper defined by greta arrays
min <- as_data(iris$Sepal.Length)
max <- min ^ 2
d <- min + variable(0, 1, dim = nrow(iris)) * (max - min)
# }