Statistics.Distributions.Binomial (statistics v0.6.3)

Binomial distribution.

This models the expected outcome of a number of binary trials, each with known probability, (often called a Bernoulli trial)

Summary

Functions

The cumulative density function

The probability mass function.

The percentile-point function

Draw a random number from a binomial distribution

Functions

@spec cdf(non_neg_integer(), number()) :: (... -> any())

The cumulative density function

Examples

iex> Statistics.Distributions.Binomial.cdf(4, 0.5).(2)
0.6875
@spec pmf(non_neg_integer(), number()) :: (... -> any())

The probability mass function.

Note that calling the mass function with a Float will return nil because this is a discrete probability distribution which only includes integer values.

Examples

iex> Statistics.Distributions.Binomial.pmf(4, 0.5).(2)
0.375
iex> Statistics.Distributions.Binomial.pmf(4, 0.5).(0.2)
nil
@spec ppf(non_neg_integer(), number()) :: (... -> any())

The percentile-point function

Examples

iex> Statistics.Distributions.Binomial.ppf(10, 0.5).(0.5)
5
@spec rand(non_neg_integer(), number()) :: non_neg_integer()

Draw a random number from a binomial distribution

Uses the rejection sampling method and returns a rounded Float.

Examples

iex> Statistics.Distributions.Binomial.rand(10, 0.5)
5.0