This bijector maps inputs from [0, inf] to [0, 1]. The inverse of the bijector applied to a uniform random variable X ~ U(0, 1) gives back a random variable with the Weibull distribution:

Y ~ Weibull(scale, concentration)
pdf(y; scale, concentration, y >= 0) =
  (concentration / scale) * (y / scale)**(concentration - 1) *
    exp(-(y / scale)**concentration)
tfb_weibull_cdf(
  scale = 1,
  concentration = 1,
  validate_args = FALSE,
  name = "weibull_cdf"
)

Arguments

scale

Positive Float-type Tensor that is the same dtype and is broadcastable with concentration. This is l in Y = g(X) = 1 - exp((-x / l) ** k).

concentration

Positive Float-type Tensor that is the same dtype and is broadcastable with scale. This is k in Y = g(X) = 1 - exp((-x / l) ** k).

validate_args

Logical, default FALSE. Whether to validate input with asserts. If validate_args is FALSE, and the inputs are invalid, correct behavior is not guaranteed.

name

name prefixed to Ops created by this class.

Value

a bijector instance.

Details

Likwewise, the forward of this bijector is the Weibull distribution CDF.

See also