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.
exposurearrat_like: Currently this is total exposure time of the count variable.
probfloat in (0, 1): 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: Exposure of the new or predicted observation.
methodstr: 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 in (0, 1): Significance level for the confidence interval of the estimate of the Poisson rate. Nominal coverage of the confidence interval is 1 - alpha.
alternative{“two-sider”, “larger”, “smaller”): 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) of limits of tolerance interval.: The tolerance interval is a closed interval, that is both low and upp are in the interval.