View source: R/truncated_poly_gamma.R
| bf.dist.truncated_polya_gamma | R Documentation |
This distribution is a truncated version of the PolyaGamma distribution, defined over the interval [0, truncation_point]. It is often used in Bayesian non-parametric models.
p(x) = \frac{1}{Z} \exp\left( \sum_{n=0}^{N} \left( \log(2n+1) - 1.5 \log(x) - \frac{(2n+1)^2}{4x} \right) \right)
bf.dist.truncated_polya_gamma(
batch_shape = c(),
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
)
batch_shape |
A numeric vector specifying the shape of the batch dimension. |
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 numeric vector, matrix, or array (e.g., a JAX array) of boolean values 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 (e.g., 'c(10)') used to shape the distribution. 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 |
An integer representing the number of batch dimensions to reinterpret as event dimensions. |
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. |
- When sample=FALSE, a BI Truncated PolyaGamma distribution object (for model building).
- When sample=TRUE, a JAX array of samples drawn from the Truncated PolyaGamma distribution (for direct sampling).
- When create_obj=TRUE, the raw BI distribution object (for advanced use cases).
library(BayesForge)
m=importBF(platform='cpu')
bf.dist.truncated_polya_gamma(batch_shape = c(), sample = TRUE)
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