Safe Haskell	Safe-Inferred
Language	Haskell2010

Statistics.ConfidenceInt

Contents

References

Description

Calculation of confidence intervals

Synopsis

poissonCI :: CL Double -> Int -> Estimate ConfInt Double
poissonNormalCI :: Int -> Estimate NormalErr Double
binomialCI :: CL Double -> Int -> Int -> Estimate ConfInt Double
naiveBinomialCI :: Int -> Int -> Estimate NormalErr Double

Documentation

poissonCI :: CL Double -> Int -> Estimate ConfInt Double Source #

Calculate confidence intervals for Poisson-distributed value for single measurement. These are exact confidence intervals

poissonNormalCI :: Int -> Estimate NormalErr Double Source #

Calculate confidence intervals for Poisson-distributed value using normal approximation

binomialCI Source #

Arguments

:: CL Double
-> Int	Number of trials
-> Int	Number of successes
-> Estimate ConfInt Double

Clopper-Pearson confidence interval also known as exact confidence intervals.

naiveBinomialCI Source #

Arguments

:: Int	Number of trials
-> Int	Number of successes
-> Estimate NormalErr Double

Calculate confidence interval using normal approximation. Note that this approximation breaks down when p is either close to 0 or to 1. In particular if np < 5 or 1 - np < 5 this approximation shouldn't be used.

References

Clopper, C.; Pearson, E. S. (1934). "The use of confidence or fiducial limits illustrated in the case of the binomial". Biometrika 26: 404–413. doi:10.1093biomet26.4.404
Brown, Lawrence D.; Cai, T. Tony; DasGupta, Anirban (2001). "Interval Estimation for a Binomial Proportion". Statistical Science 16 (2): 101–133. doi:10.1214ss1009213286. MR 1861069. Zbl 02068924.