bf.dist.half_cauchy: HalfCauchy Distribution

In BayesForge: Bayesian Inference using 'numpyro' and 'XLA'

HalfCauchy Distribution

Description

The HalfCauchy distribution is a probability distribution that is half of the Cauchy distribution. It is defined on the positive real numbers and is often used in situations where only positive values are relevant.

Usage

bf.dist.half_cauchy(
  scale = 1,
  validate_args = py_none(),
  name = "x",
  obs = py_none(),
  mask = py_none(),
  sample = FALSE,
  seed = py_none(),
  shape = c(),
  event = 0,
  create_obj = FALSE,
  to_jax = TRUE
)

Arguments

scale	A numeric vector representing the scale parameter of the Cauchy distribution. Must be positive.
validate_args	Logical: Whether to validate parameter values. Defaults to 'reticulate::py_none()'.
name	A character string representing the name of the random variable within a model. This is used to uniquely identify the variable. Defaults to 'x'.
obs	A numeric vector or array of observed values. If provided, the random variable is conditioned on these values. If 'NULL', the variable is treated as a latent (unobserved) variable. Defaults to 'NULL'.
mask	A logical vector, optionally used to mask observations.
sample	A logical value that controls the function's behavior. If 'TRUE', the function will directly draw samples from the distribution. If 'FALSE', it will create a random variable within a model. Defaults to 'FALSE'.
seed	An integer used to set the random seed for reproducibility when 'sample = TRUE'. This argument has no effect when 'sample = FALSE', as randomness is handled by the model's inference engine. Defaults to 0.
shape	A numeric vector used for shaping. When ‘sample=False' (model building), this is used with '.expand(shape)' to set the distribution’s batch shape. When 'sample=True' (direct sampling), this is used as 'sample_shape' to draw a raw JAX array of the given shape.
event	Integer specifying the number of batch dimensions to reinterpret as event dimensions (used in model building).
create_obj	Logical; If 'TRUE', returns the raw BI distribution object instead of creating a sample site.
to_jax	Boolean. Indicates whether to return a JAX array or not.

Value

- When sample=FALSE, a BI HalfCauchy distribution object (for model building).

- When sample=TRUE, a JAX array of samples drawn from the HalfCauchy distribution (for direct sampling).

- When create_obj=TRUE, the raw BI distribution object (for advanced use cases).

See Also

This is a wrapper of https://num.pyro.ai/en/stable/distributions.html#halfcauchy

Examples

library(BayesForge)
m=importBF(platform='cpu')
bf.dist.half_cauchy(sample = TRUE)

BayesForge documentation built on June 9, 2026, 1:09 a.m.