Skip to main content

methods associated with poisson binomial distribution

Project description

Poisson Binomial

The Poisson binomial distribution is the discrete probability distribution of a sum of independent Bernoulli trials that are not necessarily identically distributed. That is, it is the number of successes in a sequence of n independent yes/no experiments where the success probabilities vary.

The package contains a single class PoissonBinomial.

Parameters: p : array-like the probabilities of success for each of the Bernouilli trials

Attributes: pmf : array-like probability mass function the probability of n successes where 0<=n<=len(p) cdf : array-like, cumulative distribution function the probability of n or less successes where 0<=n<=len(p)

Methods:

x_or_less(x) : float, probability of achieving x or less successes
x_or_more(x) : float, probability of achieving x or more successes

The class PoissonBinomial implements a closed-form expression for the cdf of the Poisson binomial distribution,derived in "On computing the distribution function for the Poisson binomial distribution" by Yili Hong (2013).

The approach is based on finding the discrete fourier transform function for the characteristic function (CF) for the Poisson binomial distribution.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

poisson_binomial-0.0.1.tar.gz (2.1 kB view hashes)

Uploaded source

Built Distribution

poisson_binomial-0.0.1-py3-none-any.whl (3.4 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page