Transform to probability values

Maps unconstrained values to (0, 1) via the sigmoid function. Use this for probability parameters.

Usage

probability(x)

Arguments

x

Unconstrained value (scalar, vector, or value object)

Value

Value in (0, 1)

Details

The transformation is: probability(x) = 1 / (1 + exp(-x)) = sigmoid(x)

For optimization:

  result <- fit(
    function(logit_p) {
      p <- probability(logit_p)
      loglik_bernoulli(p, data)
    },
    params = c(logit_p = 0)  # sigmoid(0) = 0.5
  )
  # To recover p: sigmoid(coef(result)["logit_p"])

Examples

if (FALSE) { # \dontrun{
# Parameter that must be in (0, 1)
logit_p <- val(2)
p <- probability(logit_p)  # sigmoid(2) ≈ 0.88
get_data(p)
} # }