| Copyright | (c) 2011 Aleksey Khudyakov |
|---|---|
| License | BSD3 |
| Maintainer | bos@serpentine.com |
| Stability | experimental |
| Portability | portable |
| Safe Haskell | None |
| Language | Haskell98 |
Statistics.Test.KolmogorovSmirnov
Description
Kolmogov-Smirnov tests are non-parametric tests for assessing whether given sample could be described by distribution or whether two samples have the same distribution. It's only applicable to continuous distributions.
- kolmogorovSmirnovTest :: (Distribution d, Vector v Double) => d -> v Double -> Maybe (Test ())
- kolmogorovSmirnovTestCdf :: Vector v Double => (Double -> Double) -> v Double -> Maybe (Test ())
- kolmogorovSmirnovTest2 :: Vector v Double => v Double -> v Double -> Maybe (Test ())
- kolmogorovSmirnovCdfD :: Vector v Double => (Double -> Double) -> v Double -> Double
- kolmogorovSmirnovD :: (Distribution d, Vector v Double) => d -> v Double -> Double
- kolmogorovSmirnov2D :: Vector v Double => v Double -> v Double -> Double
- kolmogorovSmirnovProbability :: Int -> Double -> Double
- module Statistics.Test.Types
Kolmogorov-Smirnov test
kolmogorovSmirnovTest Source #
Arguments
| :: (Distribution d, Vector v Double) | |
| => d | Distribution |
| -> v Double | Data sample |
| -> Maybe (Test ()) |
Check that sample could be described by distribution. Returns
Nothing is sample is empty
This test uses Marsaglia-Tsang-Wang exact algorithm for calculation of p-value.
kolmogorovSmirnovTestCdf Source #
Arguments
| :: Vector v Double | |
| => (Double -> Double) | CDF of distribution |
| -> v Double | Data sample |
| -> Maybe (Test ()) |
Variant of kolmogorovSmirnovTest which uses CFD in form of
function.
kolmogorovSmirnovTest2 Source #
Two sample Kolmogorov-Smirnov test. It tests whether two data samples could be described by the same distribution without making any assumptions about it. If either of samples is empty returns Nothing.
This test uses approximate formula for computing p-value.
Evaluate statistics
kolmogorovSmirnovCdfD Source #
Calculate Kolmogorov's statistic D for given cumulative distribution function (CDF) and data sample. If sample is empty returns 0.
Arguments
| :: (Distribution d, Vector v Double) | |
| => d | Distribution |
| -> v Double | Sample |
| -> Double |
Calculate Kolmogorov's statistic D for given cumulative distribution function (CDF) and data sample. If sample is empty returns 0.
Calculate Kolmogorov's statistic D for two data samples. If either of samples is empty returns 0.
Probablities
kolmogorovSmirnovProbability Source #
Calculate cumulative probability function for Kolmogorov's distribution with n parameters or probability of getting value smaller than d with n-elements sample.
It uses algorithm by Marsgalia et. al. and provide at least 7-digit accuracy.
References
- G. Marsaglia, W. W. Tsang, J. Wang (2003) Evaluating Kolmogorov's distribution, Journal of Statistical Software, American Statistical Association, vol. 8(i18).
module Statistics.Test.Types