bf.dist.left_truncated_distribution: Samples from a left-truncated distribution.

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

Samples from a left-truncated distribution.

Description

A left-truncated distribution is a probability distribution obtained by restricting the support of another distribution to values greater than a specified lower bound. This is useful when dealing with data that is known to be greater than a certain value. All the "mass" below (or equal to) (a) is excluded (not just unobserved, but removed from the sample/analysis).

f(x) = \begin{cases} \frac{f(x)}{P(X > \text{low})} & \text{if } x > \text{low} \\ 0 & \text{otherwise} \end{cases}

Usage

bf.dist.left_truncated_distribution(
  base_dist,
  low = 0,
  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

base_dist	The base distribution to truncate. Must be univariate and have real support.
low	The lower truncation bound. Values less than this are excluded from the distribution.
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	An optional boolean vector 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. 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	The number of batch dimensions to reinterpret as event dimensions (used in model building).
create_obj	A logical value. 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 LeftTruncatedDistribution distribution object (for model building).

- When sample=TRUE: A JAX array of samples drawn from the LeftTruncatedDistribution 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#lefttruncateddistribution

Examples

library(BayesForge)
m=importBF(platform='cpu')
bf.dist.left_truncated_distribution(
base_dist = bf.dist.normal(loc = 1, scale = 10 ,  create_obj = TRUE),
sample = TRUE)

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