scvi.distributions.NegativeBinomial¶

class scvi.distributions.NegativeBinomial(total_count=None, probs=None, logits=None, mu=None, theta=None, validate_args=False)[source]

Negative binomial distribution.

One of the following parameterizations must be provided:

(1), (total_count, probs) where total_count is the number of failures until the experiment is stopped and probs the success probability. (2), (mu, theta) parameterization, which is the one used by scvi-tools. These parameters respectively control the mean and inverse dispersion of the distribution.

In the (mu, theta) parameterization, samples from the negative binomial are generated as follows:

1. $$w \sim \textrm{Gamma}(\underbrace{\theta}_{\text{shape}}, \underbrace{\theta/\mu}_{\text{rate}})$$

2. $$x \sim \textrm{Poisson}(w)$$

Parameters
total_count : (default: None)

Number of failures until the experiment is stopped.

probs : (default: None)

The success probability.

mu : (default: None)

Mean of the distribution.

theta : (default: None)

Inverse dispersion.

validate_args : boolbool (default: False)

Raise ValueError if arguments do not match constraints

Attributes

 arg_constraints batch_shape Returns the shape over which parameters are batched. event_shape Returns the shape of a single sample (without batching). has_enumerate_support has_rsample mean Returns the mean of the distribution. stddev Returns the standard deviation of the distribution. support variance Returns the variance of the distribution.

Methods

 cdf(value) Returns the cumulative density/mass function evaluated at value. Returns entropy of distribution, batched over batch_shape. enumerate_support([expand]) Returns tensor containing all values supported by a discrete distribution. expand(batch_shape[, _instance]) Returns a new distribution instance (or populates an existing instance provided by a derived class) with batch dimensions expanded to batch_shape. icdf(value) Returns the inverse cumulative density/mass function evaluated at value. log_prob(value) Returns the log of the probability density/mass function evaluated at value. Returns perplexity of distribution, batched over batch_shape. rsample([sample_shape]) Generates a sample_shape shaped reparameterized sample or sample_shape shaped batch of reparameterized samples if the distribution parameters are batched. sample([sample_shape]) Generates a sample_shape shaped sample or sample_shape shaped batch of samples if the distribution parameters are batched. Generates n samples or n batches of samples if the distribution parameters are batched. Sets whether validation is enabled or disabled.