Copyright	(c) 2009-2014 Bryan O'Sullivan
License	BSD-style
Maintainer	bos@serpentine.com
Stability	experimental
Portability	GHC
Safe Haskell	Trustworthy
Language	Haskell2010

Criterion.Analysis

Description

Analysis code for benchmarks.

Synopsis

data Outliers = Outliers {
- samplesSeen :: !Int64
- lowSevere :: !Int64
- lowMild :: !Int64
- highMild :: !Int64
- highSevere :: !Int64
}
data OutlierEffect
- = Unaffected
- | Slight
- | Moderate
- | Severe
data OutlierVariance = OutlierVariance {
- ovEffect :: OutlierEffect
- ovDesc :: String
- ovFraction :: Double
}
data SampleAnalysis = SampleAnalysis {
- anRegress :: [Regression]
- anMean :: Estimate ConfInt Double
- anStdDev :: Estimate ConfInt Double
- anOutlierVar :: OutlierVariance
}
analyseSample :: Int -> String -> Vector Measured -> ExceptT String Criterion Report
scale :: Double -> SampleAnalysis -> SampleAnalysis
analyseMean :: Sample -> Int -> Criterion Double
countOutliers :: Outliers -> Int64
classifyOutliers :: Sample -> Outliers
noteOutliers :: Outliers -> Criterion ()
outlierVariance :: Estimate ConfInt Double -> Estimate ConfInt Double -> Double -> OutlierVariance
resolveAccessors :: [String] -> Either String [(String, Measured -> Maybe Double)]
validateAccessors :: [String] -> String -> Either String [(String, Measured -> Maybe Double)]
regress :: GenIO -> [String] -> String -> Vector Measured -> ExceptT String Criterion Regression

Documentation

data Outliers Source #

Outliers from sample data, calculated using the boxplot technique.

Constructors

Outliers

Fields

samplesSeen :: !Int64
lowSevere :: !Int64
More than 3 times the interquartile range (IQR) below the first quartile.
lowMild :: !Int64
Between 1.5 and 3 times the IQR below the first quartile.
highMild :: !Int64
Between 1.5 and 3 times the IQR above the third quartile.
highSevere :: !Int64
More than 3 times the IQR above the third quartile.

Instances

Instances details

FromJSON Outliers Source #

Instance details

Defined in Criterion.Types

Methods

parseJSON :: Value -> Parser Outliers #

parseJSONList :: Value -> Parser [Outliers] #

omittedField :: Maybe Outliers #

ToJSON Outliers Source #

Instance details

Defined in Criterion.Types

Methods

toJSON :: Outliers -> Value #

toEncoding :: Outliers -> Encoding #

toJSONList :: [Outliers] -> Value #

toEncodingList :: [Outliers] -> Encoding #

omitField :: Outliers -> Bool #

Data Outliers Source #

Instance details

Defined in Criterion.Types

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> Outliers -> c Outliers #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c Outliers #

toConstr :: Outliers -> Constr #

dataTypeOf :: Outliers -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c Outliers) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c Outliers) #

gmapT :: (forall b. Data b => b -> b) -> Outliers -> Outliers #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> Outliers -> r #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> Outliers -> r #

gmapQ :: (forall d. Data d => d -> u) -> Outliers -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> Outliers -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> Outliers -> m Outliers #

Monoid Outliers Source #

Instance details

Defined in Criterion.Types

Methods

mempty :: Outliers #

mappend :: Outliers -> Outliers -> Outliers #

mconcat :: [Outliers] -> Outliers #

Semigroup Outliers Source #

Instance details

Defined in Criterion.Types

Methods

(<>) :: Outliers -> Outliers -> Outliers #

sconcat :: NonEmpty Outliers -> Outliers #

stimes :: Integral b => b -> Outliers -> Outliers #

Generic Outliers Source #

Instance details

Defined in Criterion.Types

Associated Types

type Rep Outliers

Instance details

Defined in Criterion.Types

type Rep Outliers = D1 ('MetaData "Outliers" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "Outliers" 'PrefixI 'True) ((S1 ('MetaSel ('Just "samplesSeen") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: S1 ('MetaSel ('Just "lowSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)) :*: (S1 ('MetaSel ('Just "lowMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: (S1 ('MetaSel ('Just "highMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: S1 ('MetaSel ('Just "highSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)))))

Methods

from :: Outliers -> Rep Outliers x #

to :: Rep Outliers x -> Outliers #

Read Outliers Source #

Instance details

Defined in Criterion.Types

Methods

readsPrec :: Int -> ReadS Outliers #

readList :: ReadS [Outliers] #

readPrec :: ReadPrec Outliers #

readListPrec :: ReadPrec [Outliers] #

Show Outliers Source #

Instance details

Defined in Criterion.Types

Methods

showsPrec :: Int -> Outliers -> ShowS #

show :: Outliers -> String #

showList :: [Outliers] -> ShowS #

Binary Outliers Source #

Instance details

Defined in Criterion.Types

Methods

put :: Outliers -> Put #

get :: Get Outliers #

putList :: [Outliers] -> Put #

NFData Outliers Source #

Instance details

Defined in Criterion.Types

Methods

rnf :: Outliers -> () #

Eq Outliers Source #

Instance details

Defined in Criterion.Types

Methods

(==) :: Outliers -> Outliers -> Bool #

(/=) :: Outliers -> Outliers -> Bool #

type Rep Outliers Source #

Instance details

Defined in Criterion.Types

type Rep Outliers = D1 ('MetaData "Outliers" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "Outliers" 'PrefixI 'True) ((S1 ('MetaSel ('Just "samplesSeen") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: S1 ('MetaSel ('Just "lowSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)) :*: (S1 ('MetaSel ('Just "lowMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: (S1 ('MetaSel ('Just "highMild") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64) :*: S1 ('MetaSel ('Just "highSevere") 'NoSourceUnpackedness 'SourceStrict 'DecidedStrict) (Rec0 Int64)))))

data OutlierEffect Source #

A description of the extent to which outliers in the sample data affect the sample mean and standard deviation.

Constructors

Unaffected

Less than 1% effect.

Slight

Between 1% and 10%.

Moderate

Between 10% and 50%.

Severe

Above 50% (i.e. measurements are useless).

Instances

Instances details

FromJSON OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

parseJSON :: Value -> Parser OutlierEffect #

parseJSONList :: Value -> Parser [OutlierEffect] #

omittedField :: Maybe OutlierEffect #

ToJSON OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

toJSON :: OutlierEffect -> Value #

toEncoding :: OutlierEffect -> Encoding #

toJSONList :: [OutlierEffect] -> Value #

toEncodingList :: [OutlierEffect] -> Encoding #

omitField :: OutlierEffect -> Bool #

Data OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> OutlierEffect -> c OutlierEffect #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c OutlierEffect #

toConstr :: OutlierEffect -> Constr #

dataTypeOf :: OutlierEffect -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c OutlierEffect) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c OutlierEffect) #

gmapT :: (forall b. Data b => b -> b) -> OutlierEffect -> OutlierEffect #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> OutlierEffect -> r #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> OutlierEffect -> r #

gmapQ :: (forall d. Data d => d -> u) -> OutlierEffect -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> OutlierEffect -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierEffect -> m OutlierEffect #

Generic OutlierEffect Source #

Instance details

Defined in Criterion.Types

Associated Types

type Rep OutlierEffect

Instance details

Defined in Criterion.Types

type Rep OutlierEffect = D1 ('MetaData "OutlierEffect" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) ((C1 ('MetaCons "Unaffected" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Slight" 'PrefixI 'False) (U1 :: Type -> Type)) :+: (C1 ('MetaCons "Moderate" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Severe" 'PrefixI 'False) (U1 :: Type -> Type)))

Methods

from :: OutlierEffect -> Rep OutlierEffect x #

to :: Rep OutlierEffect x -> OutlierEffect #

Read OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

readsPrec :: Int -> ReadS OutlierEffect #

readList :: ReadS [OutlierEffect] #

readPrec :: ReadPrec OutlierEffect #

readListPrec :: ReadPrec [OutlierEffect] #

Show OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

showsPrec :: Int -> OutlierEffect -> ShowS #

show :: OutlierEffect -> String #

showList :: [OutlierEffect] -> ShowS #

Binary OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

put :: OutlierEffect -> Put #

get :: Get OutlierEffect #

putList :: [OutlierEffect] -> Put #

NFData OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

rnf :: OutlierEffect -> () #

Eq OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

(==) :: OutlierEffect -> OutlierEffect -> Bool #

(/=) :: OutlierEffect -> OutlierEffect -> Bool #

Ord OutlierEffect Source #

Instance details

Defined in Criterion.Types

Methods

compare :: OutlierEffect -> OutlierEffect -> Ordering #

(<) :: OutlierEffect -> OutlierEffect -> Bool #

(<=) :: OutlierEffect -> OutlierEffect -> Bool #

(>) :: OutlierEffect -> OutlierEffect -> Bool #

(>=) :: OutlierEffect -> OutlierEffect -> Bool #

max :: OutlierEffect -> OutlierEffect -> OutlierEffect #

min :: OutlierEffect -> OutlierEffect -> OutlierEffect #

type Rep OutlierEffect Source #

Instance details

Defined in Criterion.Types

type Rep OutlierEffect = D1 ('MetaData "OutlierEffect" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) ((C1 ('MetaCons "Unaffected" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Slight" 'PrefixI 'False) (U1 :: Type -> Type)) :+: (C1 ('MetaCons "Moderate" 'PrefixI 'False) (U1 :: Type -> Type) :+: C1 ('MetaCons "Severe" 'PrefixI 'False) (U1 :: Type -> Type)))

data OutlierVariance Source #

Analysis of the extent to which outliers in a sample affect its standard deviation (and to some extent, its mean).

Constructors

OutlierVariance

Fields

ovEffect :: OutlierEffect
Qualitative description of effect.
ovDesc :: String
Brief textual description of effect.
ovFraction :: Double
Quantitative description of effect (a fraction between 0 and 1).

Instances

Instances details

FromJSON OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

parseJSON :: Value -> Parser OutlierVariance #

parseJSONList :: Value -> Parser [OutlierVariance] #

omittedField :: Maybe OutlierVariance #

ToJSON OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

toJSON :: OutlierVariance -> Value #

toEncoding :: OutlierVariance -> Encoding #

toJSONList :: [OutlierVariance] -> Value #

toEncodingList :: [OutlierVariance] -> Encoding #

omitField :: OutlierVariance -> Bool #

Data OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> OutlierVariance -> c OutlierVariance #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c OutlierVariance #

toConstr :: OutlierVariance -> Constr #

dataTypeOf :: OutlierVariance -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c OutlierVariance) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c OutlierVariance) #

gmapT :: (forall b. Data b => b -> b) -> OutlierVariance -> OutlierVariance #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> OutlierVariance -> r #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> OutlierVariance -> r #

gmapQ :: (forall d. Data d => d -> u) -> OutlierVariance -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> OutlierVariance -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> OutlierVariance -> m OutlierVariance #

Generic OutlierVariance Source #

Instance details

Defined in Criterion.Types

Associated Types

type Rep OutlierVariance

Instance details

Defined in Criterion.Types

type Rep OutlierVariance = D1 ('MetaData "OutlierVariance" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "OutlierVariance" 'PrefixI 'True) (S1 ('MetaSel ('Just "ovEffect") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierEffect) :*: (S1 ('MetaSel ('Just "ovDesc") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 String) :*: S1 ('MetaSel ('Just "ovFraction") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Double))))

Methods

from :: OutlierVariance -> Rep OutlierVariance x #

to :: Rep OutlierVariance x -> OutlierVariance #

Read OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

readsPrec :: Int -> ReadS OutlierVariance #

readList :: ReadS [OutlierVariance] #

readPrec :: ReadPrec OutlierVariance #

readListPrec :: ReadPrec [OutlierVariance] #

Show OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

showsPrec :: Int -> OutlierVariance -> ShowS #

show :: OutlierVariance -> String #

showList :: [OutlierVariance] -> ShowS #

Binary OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

put :: OutlierVariance -> Put #

get :: Get OutlierVariance #

putList :: [OutlierVariance] -> Put #

NFData OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

rnf :: OutlierVariance -> () #

Eq OutlierVariance Source #

Instance details

Defined in Criterion.Types

Methods

(==) :: OutlierVariance -> OutlierVariance -> Bool #

(/=) :: OutlierVariance -> OutlierVariance -> Bool #

type Rep OutlierVariance Source #

Instance details

Defined in Criterion.Types

type Rep OutlierVariance = D1 ('MetaData "OutlierVariance" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "OutlierVariance" 'PrefixI 'True) (S1 ('MetaSel ('Just "ovEffect") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierEffect) :*: (S1 ('MetaSel ('Just "ovDesc") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 String) :*: S1 ('MetaSel ('Just "ovFraction") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Double))))

data SampleAnalysis Source #

Result of a bootstrap analysis of a non-parametric sample.

Constructors

SampleAnalysis

Fields

anRegress :: [Regression]
Estimates calculated via linear regression.
anMean :: Estimate ConfInt Double
Estimated mean.
anStdDev :: Estimate ConfInt Double
Estimated standard deviation.
anOutlierVar :: OutlierVariance
Description of the effects of outliers on the estimated variance.

Instances

Instances details

FromJSON SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

parseJSON :: Value -> Parser SampleAnalysis #

parseJSONList :: Value -> Parser [SampleAnalysis] #

omittedField :: Maybe SampleAnalysis #

ToJSON SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

toJSON :: SampleAnalysis -> Value #

toEncoding :: SampleAnalysis -> Encoding #

toJSONList :: [SampleAnalysis] -> Value #

toEncodingList :: [SampleAnalysis] -> Encoding #

omitField :: SampleAnalysis -> Bool #

Generic SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Associated Types

type Rep SampleAnalysis

Instance details

Defined in Criterion.Types

type Rep SampleAnalysis = D1 ('MetaData "SampleAnalysis" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "SampleAnalysis" 'PrefixI 'True) ((S1 ('MetaSel ('Just "anRegress") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 [Regression]) :*: S1 ('MetaSel ('Just "anMean") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double))) :*: (S1 ('MetaSel ('Just "anStdDev") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double)) :*: S1 ('MetaSel ('Just "anOutlierVar") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierVariance))))

Methods

from :: SampleAnalysis -> Rep SampleAnalysis x #

to :: Rep SampleAnalysis x -> SampleAnalysis #

Read SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

readsPrec :: Int -> ReadS SampleAnalysis #

readList :: ReadS [SampleAnalysis] #

readPrec :: ReadPrec SampleAnalysis #

readListPrec :: ReadPrec [SampleAnalysis] #

Show SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

showsPrec :: Int -> SampleAnalysis -> ShowS #

show :: SampleAnalysis -> String #

showList :: [SampleAnalysis] -> ShowS #

Binary SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

put :: SampleAnalysis -> Put #

get :: Get SampleAnalysis #

putList :: [SampleAnalysis] -> Put #

NFData SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

rnf :: SampleAnalysis -> () #

Eq SampleAnalysis Source #

Instance details

Defined in Criterion.Types

Methods

(==) :: SampleAnalysis -> SampleAnalysis -> Bool #

(/=) :: SampleAnalysis -> SampleAnalysis -> Bool #

type Rep SampleAnalysis Source #

Instance details

Defined in Criterion.Types

type Rep SampleAnalysis = D1 ('MetaData "SampleAnalysis" "Criterion.Types" "criterion-1.6.4.1-K8urswSQARiCV3c9gCG1B5" 'False) (C1 ('MetaCons "SampleAnalysis" 'PrefixI 'True) ((S1 ('MetaSel ('Just "anRegress") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 [Regression]) :*: S1 ('MetaSel ('Just "anMean") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double))) :*: (S1 ('MetaSel ('Just "anStdDev") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (Estimate ConfInt Double)) :*: S1 ('MetaSel ('Just "anOutlierVar") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 OutlierVariance))))

analyseSample Source #

Arguments

:: Int

Experiment number.

-> String

Experiment name.

-> Vector Measured

Sample data.

-> ExceptT String Criterion Report

Perform an analysis of a measurement.

scale Source #

Arguments

:: Double

Value to multiply by.

-> SampleAnalysis

Multiply the Estimates in an analysis by the given value, using scale .

analyseMean Source #

Arguments

:: Sample

-> Int

Number of iterations used to compute the sample.

-> Criterion Double

Display the mean of a Sample , and characterise the outliers present in the sample.

countOutliers :: Outliers -> Int64 Source #

Count the total number of outliers in a sample.

classifyOutliers :: Sample -> Outliers Source #

Classify outliers in a data set, using the boxplot technique.

noteOutliers :: Outliers -> Criterion () Source #

Display a report of the Outliers present in a Sample .

outlierVariance Source #

Arguments

:: Estimate ConfInt Double

Bootstrap estimate of sample mean.

-> Estimate ConfInt Double

Bootstrap estimate of sample standard deviation.

-> Double

Number of original iterations.

-> OutlierVariance

Compute the extent to which outliers in the sample data affect the sample mean and standard deviation.

resolveAccessors :: [String] -> Either String [(String, Measured -> Maybe Double)] Source #

Given a list of accessor names (see measureKeys ), return either a mapping from accessor name to function or an error message if any names are wrong.

validateAccessors Source #

Arguments

:: [String]

Predictor names.

-> String

Responder name.

-> Either String [(String, Measured -> Maybe Double)]

Given predictor and responder names, do some basic validation, then hand back the relevant accessors.

regress Source #

Arguments

:: GenIO

-> [String]