statsmodels.stats.rates.confint_quantile_poisson

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

confidence interval for quantile of poisson random variable

Parameters:

  • count (array_like) – Observed count, number of events.

  • exposure (arrat_like) – Currently this is total exposure time of the count variable.

  • prob (float in (0, 1)) – Probability for the quantile, e.g. 0.95 to get the upper 95% quantile. With known mean mu, the quantile would be poisson.ppf(prob, mu).

  • exposure_new (float) – Exposure of the new or predicted observation.

  • method (str) – 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.

  • alpha (float 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 confidence interval is a closed interval, that is both low and

  • upp are in the interval.

See also

confint_poisson, tolerance_int_poisson

References

Hahn, Gerald J, and William Q Meeker. 2010. Statistical Intervals: A Guide for Practitioners.