statsmodels.stats.rates.tolerance_int_poisson#

statsmodels.stats.rates.tolerance_int_poisson(count, exposure, prob=0.95, exposure_new=1.0, method=None, alpha=0.05, alternative='two-sided')[source]#

Tolerance interval for a poisson observation

Parameters:

countarray_like: Observed count, number of events.
exposurearray_like: Currently this is total exposure time of the count variable.
probfloat or array_like in (0, 1), optional: Probability of poisson interval, often called “content”. With known parameters, each tail would have at most probability 1 - prob / 2 in the two-sided interval.
exposure_newfloat, optional: Exposure of the new or predicted observation.
methodstr, optional: Method to used for confidence interval of the estimate of the poisson rate, used in confint_poisson. This is required, there is currently no default method.
alphafloat or array_like in (0, 1), optional: Significance level for the confidence interval of the estimate of the Poisson rate. Nominal coverage of the confidence interval is 1 - alpha.
alternative{“two-sided”, “larger”, “smaller”}, optional: The tolerance interval can be two-sided or one-sided. Alternative “larger” provides the upper bound of the confidence interval, larger counts are outside the interval.

Returns:

tuple (low, upp): Limits of tolerance interval. The tolerance interval is a closed interval, that is both low and upp are in the interval.