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tfb_weibull

ComputesY = g(X) = 1 - exp((-X / scale) ** concentration) where X >= 0


Description

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:

Usage

tfb_weibull(
  scale = 1,
  concentration = 1,
  validate_args = FALSE,
  name = "weibull"
)

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.

Details

Y ~ Weibull(scale, concentration) pdf(y; scale, concentration, y >= 0) = (concentration / scale) * (y / scale)**(concentration - 1) * exp(-(y / scale)**concentration)

Value

a bijector instance.

See Also


tfprobability

Interface to 'TensorFlow Probability'

v0.11.0.0
Apache License (>= 2.0)
Authors
Sigrid Keydana [aut, cre], Daniel Falbel [ctb], Kevin Kuo [ctb] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Initial release

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