confidence_interval#
- EmpiricalDistributionFunction.confidence_interval(confidence_level=0.95, *, method='linear')[source]#
- Compute a confidence interval around the CDF/SF point estimate - Parameters:
- confidence_levelfloat, default: 0.95
- Confidence level for the computed confidence interval 
- methodstr, {“linear”, “log-log”}
- Method used to compute the confidence interval. Options are “linear” for the conventional Greenwood confidence interval (default) and “log-log” for the “exponential Greenwood”, log-negative-log-transformed confidence interval. 
 
- Returns:
- ciConfidenceInterval
- An object with attributes - lowand- high, instances of- EmpiricalDistributionFunctionthat represent the lower and upper bounds (respectively) of the confidence interval.
 
- ci
 - Notes - Confidence intervals are computed according to the Greenwood formula ( - method='linear') or the more recent “exponential Greenwood” formula (- method='log-log') as described in [1]. The conventional Greenwood formula can result in lower confidence limits less than 0 and upper confidence limits greater than 1; these are clipped to the unit interval. NaNs may be produced by either method; these are features of the formulas.- References [1]- Sawyer, Stanley. “The Greenwood and Exponential Greenwood Confidence Intervals in Survival Analysis.” https://www.math.wustl.edu/~sawyer/handouts/greenwood.pdf