Statistics.Resampling.Bootstrap

statistics-0.16.3.0: A library of statistical types, data, and functions

Copyright | (c) 2009 2011 Bryan O'Sullivan
License | BSD3
Maintainer | bos@serpentine.com
Stability | experimental
Portability | portable
Safe Haskell | None
Language | Haskell2010

Statistics.Resampling.Bootstrap

Contents

- References

Description

The bootstrap method for statistical inference.

Synopsis

- bootstrapBCA :: CL Double -> Sample -> [(Estimator, Bootstrap Vector Double)] -> [Estimate ConfInt Double]
- basicBootstrap :: forall (v :: Type -> Type) a. (Vector v a, Ord a, Num a) => CL Double -> Bootstrap v a -> Estimate ConfInt a

# Documentation

bootstrapBCA #

Arguments

:: CL Double | Confidence level
-> Sample | Full data sample
-> [(Estimator, Bootstrap Vector Double)] | Estimates obtained from resampled data and estimator used for this.
-> [Estimate ConfInt Double] |

Bias-corrected accelerated (BCA) bootstrap. This adjusts for both bias and skewness in the resampled distribution.

BCA algorithm is described in ch. 5 of Davison, Hinkley "Confidence intervals" in section 5.3 "Percentile method"

basicBootstrap #

Arguments

:: forall (v :: Type -> Type) a. (Vector v a, Ord a, Num a) |
=> CL Double | Confidence vector
-> Bootstrap v a | Estimate from full sample and vector of estimates obtained from resamples
-> Estimate ConfInt a |

Basic bootstrap. This method simply uses empirical quantiles for confidence interval.

# References

- Davison, A.C; Hinkley, D.V. (1997) Bootstrap methods and their application. http://statwww.epfl.ch/davison/BMA/