tfb_weibull: Computes'Y = g(X) = 1 - exp((-X / scale) ** concentration)'...

In tfprobability: Interface to 'TensorFlow Probability'

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

For usage examples see tfb_forward(), tfb_inverse(), tfb_inverse_log_det_jacobian().

Other bijectors: tfb_absolute_value(), tfb_affine_linear_operator(), tfb_affine_scalar(), tfb_affine(), tfb_ascending(), tfb_batch_normalization(), tfb_blockwise(), tfb_chain(), tfb_cholesky_outer_product(), tfb_cholesky_to_inv_cholesky(), tfb_correlation_cholesky(), tfb_cumsum(), tfb_discrete_cosine_transform(), tfb_expm1(), tfb_exp(), tfb_ffjord(), tfb_fill_scale_tri_l(), tfb_fill_triangular(), tfb_glow(), tfb_gompertz_cdf(), tfb_gumbel_cdf(), tfb_gumbel(), tfb_identity(), tfb_inline(), tfb_invert(), tfb_iterated_sigmoid_centered(), tfb_kumaraswamy_cdf(), tfb_kumaraswamy(), tfb_lambert_w_tail(), tfb_masked_autoregressive_default_template(), tfb_masked_autoregressive_flow(), tfb_masked_dense(), tfb_matrix_inverse_tri_l(), tfb_matvec_lu(), tfb_normal_cdf(), tfb_ordered(), tfb_pad(), tfb_permute(), tfb_power_transform(), tfb_rational_quadratic_spline(), tfb_rayleigh_cdf(), tfb_real_nvp_default_template(), tfb_real_nvp(), tfb_reciprocal(), tfb_reshape(), tfb_scale_matvec_diag(), tfb_scale_matvec_linear_operator(), tfb_scale_matvec_lu(), tfb_scale_matvec_tri_l(), tfb_scale_tri_l(), tfb_scale(), tfb_shifted_gompertz_cdf(), tfb_shift(), tfb_sigmoid(), tfb_sinh_arcsinh(), tfb_sinh(), tfb_softmax_centered(), tfb_softplus(), tfb_softsign(), tfb_split(), tfb_square(), tfb_tanh(), tfb_transform_diagonal(), tfb_transpose(), tfb_weibull_cdf()

tfprobability documentation built on Sept. 1, 2022, 5:07 p.m.