Poisson distribution¶

mpsci.distributions.poisson.cdf(k, lam)¶: CDF of the Poisson distribution.

mpsci.distributions.poisson.kurtosis(lam)¶: Excess kurtosis of the Poisson distribution.

mpsci.distributions.poisson.logpmf(k, lam)¶: Natural log of the probability mass function of the binomial distribution.

mpsci.distributions.poisson.mle(x, *, counts=None)¶

Maximum likelihood estimate for the Poisson distribution.

x must be a sequence of numbers that are presumed to be a sample from a Poisson distribution.

Returns lambda, the estimated parameter of the Poisson distribution.

mpsci.distributions.poisson.nll(x, lam, *, counts=None)¶

Negative log-likelihood of the Poisson distribution.

x must be a sequence of nonnegative integers.

mpsci.distributions.poisson.pmf(k, lam)¶: Probability mass function of the Poisson distribution.

mpsci.distributions.poisson.sf(k, lam)¶: Survival function of the Poisson distribution.

mpsci.distributions.poisson.skewness(lam)¶: Skewness of the Poisson distribution.

mpsci.distributions.poisson.support(lam)¶

Support of the Poisson distribution.

The support is the integers 0, 1, 2, 3, …, so the support is returned as an instance of itertools.count(start=0).

Examples

>>> from mpsci.distributions import poisson
>>> sup = poisson.support()
>>> next(sup)
0
>>> next(sup)
1

mpsci.distributions.poisson.var(lam)¶: Variance of the Poisson distribution.