statistics-0.13.3.0: A library of statistical types, data, and functions

Copyright (c) 2009 2011 Bryan O'Sullivan BSD3 bos@serpentine.com experimental portable None Haskell98

Statistics.Resampling.Bootstrap

Contents

Description

The bootstrap method for statistical inference.

Synopsis

# Documentation

data Estimate #

A point and interval estimate computed via an Estimator.

Constructors

 Estimate FieldsestPoint :: !DoublePoint estimate.estLowerBound :: !DoubleLower bound of the estimate interval (i.e. the lower bound of the confidence interval).estUpperBound :: !DoubleUpper bound of the estimate interval (i.e. the upper bound of the confidence interval).estConfidenceLevel :: !DoubleConfidence level of the confidence intervals.

Instances

 # Methods # Methodsgfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Estimate -> c Estimate #gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Estimate #dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c Estimate) #dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Estimate) #gmapT :: (forall b. Data b => b -> b) -> Estimate -> Estimate #gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Estimate -> r #gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Estimate -> r #gmapQ :: (forall d. Data d => d -> u) -> Estimate -> [u] #gmapQi :: Int -> (forall d. Data d => d -> u) -> Estimate -> u #gmapM :: Monad m => (forall d. Data d => d -> m d) -> Estimate -> m Estimate #gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Estimate -> m Estimate #gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Estimate -> m Estimate # # Methods # MethodsshowList :: [Estimate] -> ShowS # # Associated Typestype Rep Estimate :: * -> * # Methodsto :: Rep Estimate x -> Estimate # # Methodsrnf :: Estimate -> () # # MethodstoJSONList :: [Estimate] -> Value #toEncodingList :: [Estimate] -> Encoding # # Methods # Methodsput :: Estimate -> Put #putList :: [Estimate] -> Put # type Rep Estimate # type Rep Estimate = D1 (MetaData "Estimate" "Statistics.Resampling.Bootstrap" "statistics-0.13.3.0-5G6LnnwwEAsBXhZQyOoIJ5" False) (C1 (MetaCons "Estimate" PrefixI True) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "estPoint") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "estLowerBound") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double))) ((:*:) (S1 (MetaSel (Just Symbol "estUpperBound") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "estConfidenceLevel") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)))))

Arguments

 :: Double Confidence level -> Sample Sample data -> [Estimator] Estimators -> [Resample] Resampled data -> [Estimate]

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

Arguments

 :: Double Value to multiply by. -> Estimate -> Estimate

Multiply the point, lower bound, and upper bound in an Estimate by the given value.