statistics

package module
v0.0.0-...-591ec42 Latest Latest
Warning

This package is not in the latest version of its module.

 Go to latest Published: Sep 13, 2016 License: MIT Imports: 3 Imported by: 4

README 

PACKAGE DOCUMENTATION

package statistics
    import "github.com/mcgrew/gostats"



FUNCTIONS

func FirstQuartile(values []float64) float64
    Returns the data value that is the 25th percentile of a set of data.

    @param values The set of values to find the first quartile of. @return
    The first quartile data point.

func KendallCorrelation(x, y []float64) float64
    Returns the Kendall tau rank correlation coefficient of the 2 sets of
    data. Each array should be the same length and contain at least 3
    values.

    <PRE>

	x = values in the first set
	y = values in the second set
	n = number of values in each set
	Rx = the rank of the values in the first set
	Ry = the rank of the values in the second set
	Tx = the number of ties in x.
	Ty = the number of ties in y.
	concordant = The number of concordant pairs
	discordant = The number of discordant pairs
	                             concordant - discordant

    correlationValue = ---------------------------------------------

	         n*(n-1)            n*(n-1)
	sqrt( ( ------- - Tx ) * (  ------- - Ty ) )
	           2                   2

    References: <CITE>Wikipedia, the free encyclopedia (2010, March 25).

	<I>Kendall tau rank correlation coefficient</I>.
	Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient</CITE>

    </PRE>

    Parameters:

	x: The first set of values to use for the calculation.
	y: The second set of values to use for the calculation.

    Return value:

	float64: The Kendall Tau correlation value.

func Max(values []float64) float64
    Returns the maximum of a set of values. NaN values are omitted.

    @param values the set of values to find the maximum for. @return The
    maximum value in the array.

func MaxRegular(values []float64) float64
    Returns the maximum regular value in a data set. This is the largest
    value that would not be considered an outlier.

    @param values The set of values to find the maximum regular value for.
    @return The minimum regular value.

func Mean(values []float64) float64
    Finds the mean of a set of values. NaN values are omitted.

    @param values The set of values. @return The mean of those values.

func Median(values []float64) float64
    Finds the median of a set of values. NaN values are omitted.

    @param values The set to find the median of. @return The median of those
    values.

func Min(values []float64) float64
    Returns the minimum of a set of values. NaN values are omitted.

    @param values The set of values to find the minimum for. @return The
    minimum value in the array.

func MinRegular(values []float64) float64
    Returns the minimum regular value in a data set. This is the smallest
    value that would not be considered an outlier.

    @param values The set of values to find the minimum regular value for.
    @return The minimum regular value.

func PearsonCorrelation(x, y []float64) float64
    Returns the Pearson correlation coefficient of the 2 sets of values.
    Each array should be the same length and contain at least 3 values.

    <PRE>

	x = sample values in the first set
	y = sample values in the second set
	n = number of values in each set
	Sx = standard deviation of x
	Sy = standard deviation of y
	                                           _              _
	                 sum( i=0 to n-1, ( x[i] - x ) * ( y[i] - y ))

    correlationValue = -----------------------------------------------

	( n - 1 ) Sx * Sy

    References: <CITE>Wikipedia, the free encyclopedia (2010, April 13).

	<I>Correlation and Dependence</I>.
	Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Correlation#Pearson.27s_product-moment_coefficient</CITE>

    </PRE>

    Parameters:

	x: The first set of values to use for the calculation.
	y: The second set of values to use for the calculation.

    Return value:

	float64: The Pearson correlation value.

func Percentile(values []float64, percentile float64) float64

func QuartileRange(values []float64) (float64, float64)
    Finds the range of the first and third quartiles of a data set, or the
    25th to 75th percentile of a set of data.

    @param values The set of data to find the quartile range for. @return A
    range containing the 25th to 75th percentiles.

func RegularRange(values []float64) (float64, float64)
    Finds the range inside which all regular values fall (inclusive).

    @param values The set of data to find the regular range for. @return A
    range outside which all other values in the data set would be

	considered outliers.

func SpearmanCorrelation(x, y []float64) float64
    Returns the Spearman rank correlation coefficient of the 2 sets of data.
    Each array should be the same length and contain at least 3 values.

    <PRE>

	x = values in the first set
	y = values in the second set
	n = number of values in each set
	Rx = rank array of x, ie. the new locations of each element of x if x were sorted
	Ry = rank array of y, ie. the new locations of each element of y if y were sorted
	                     6 * sum( i=0 to n-1, ( Rx[i] - Ry[i] )^2 )

    correlationValue = 1 - --------------------------------------------

	n * ( n^2 - 1 )

    References: <CITE>Wikipedia, the free encyclopedia (2010, April 1).

	<I>Spearman's rank correlation coefficient</I>.
	Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Spearman's_rank_correlation_coefficient</CITE>

    <CITE>Spiegel, Murray R. (1961). Statistics, 2nd Edition (pp
    376,391-393). New York.</CITE> </PRE>

    @param x The first set of data to use for the calculation. @param y The
    second set of data to use for the calculation. @return The Spearman
    correlation value. Parameters:

	x: The first set of values to use for the calculation.
	y: The second set of values to use for the calculation.

    Return value:

	float64: The Pearson correlation value.

func StandardDeviation(values []float64) float64
    Returns the standard deviation of a set of values.

    @param values The set to find the standard deviation of. @return The
    standard deviation as a double.

func Sum(values []float64) float64
    Finds the sum of a set of values. NaN values are omitted.

    @param values The set of values. @return The sum of those values.

func TandemSort(arr, companion []float64)
    TandemSort sorts 2 arrays. It makes one call to data.Len to determine n,
    and O(n*log(n)) calls to data.Less and data.Swap. The sort is not
    guaranteed to be stable.

func ThirdQuartile(values []float64) float64
    Returns the data value that is the 75th percentile of a set of data.

    @param values The set of values to find the third quartile of. @return
    The third quartile data point.

func TripletSort(arr, companion, companion2 []float64)
    TripletSort sorts 2 arrays. It makes one call to data.Len to determine
    n, and O(n*log(n)) calls to data.Less and data.Swap. The sort is not
    guaranteed to be stable.

func WeightedMean(values, weights []float64) float64
    Finds the weighted mean of a set of values. NaN values are omitted.

    @param values The set of values. @param weights The weight for each
    value @return The mean of those values.


TYPES

type Doublet struct {
    Data      []float64
    Companion []float64
}


func (p Doublet) Len() int

func (p Doublet) Less(i, j int) bool

func (p Doublet) Swap(i, j int)


type Range struct {
    Min float64
    Max float64
}
    A type for handling a number range.



type Triplet struct {
    Data       []float64
    Companion  []float64
    Companion2 []float64
}


func (p Triplet) Len() int

func (p Triplet) Less(i, j int) bool

func (p Triplet) Swap(i, j int)

Documentation

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func FirstQuartile 

func FirstQuartile(values []float64) float64

Returns the data value that is the 25th percentile of a set of data.

@param values The set of values to find the first quartile of. @return The first quartile data point.

func KendallCorrelation 

func KendallCorrelation(x, y []float64) float64

Returns the Kendall tau rank correlation coefficient of the 2 sets of data. Each array should be the same length and contain at least 3 values.

<PRE> 

x = values in the first set
y = values in the second set
n = number of values in each set
Rx = the rank of the values in the first set
Ry = the rank of the values in the second set
Tx = the number of ties in x.
Ty = the number of ties in y.
concordant = The number of concordant pairs
discordant = The number of discordant pairs

                             concordant - discordant

correlationValue = --------------------------------------------- 

         n*(n-1)            n*(n-1)
sqrt( ( ------- - Tx ) * (  ------- - Ty ) )
           2                   2

References: <CITE>Wikipedia, the free encyclopedia (2010, March 25). 

<I>Kendall tau rank correlation coefficient</I>.
Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient</CITE>

</PRE>

Parameters: 

x: The first set of values to use for the calculation.
y: The second set of values to use for the calculation.

Return value: 

float64: The Kendall Tau correlation value.

func Max 

func Max(values []float64) float64

Returns the maximum of a set of values. NaN values are omitted.

@param values the set of values to find the maximum for. @return The maximum value in the array.

func MaxRegular 

func MaxRegular(values []float64) float64

Returns the maximum regular value in a data set. This is the largest value that would not be considered an outlier.

@param values The set of values to find the maximum regular value for. @return The minimum regular value.

func Mean 

func Mean(values []float64) float64

Finds the mean of a set of values. NaN values are omitted.

@param values The set of values. @return The mean of those values.

func Median 

func Median(values []float64) float64

Finds the median of a set of values. NaN values are omitted.

@param values The set to find the median of. @return The median of those values.

func Min 

func Min(values []float64) float64

Returns the minimum of a set of values. NaN values are omitted.

@param values The set of values to find the minimum for. @return The minimum value in the array.

func MinRegular 

func MinRegular(values []float64) float64

Returns the minimum regular value in a data set. This is the smallest value that would not be considered an outlier.

@param values The set of values to find the minimum regular value for. @return The minimum regular value.

func PearsonCorrelation 

func PearsonCorrelation(x, y []float64) float64

Returns the Pearson correlation coefficient of the 2 sets of values. Each array should be the same length and contain at least 3 values.

<PRE> 

x = sample values in the first set
y = sample values in the second set
n = number of values in each set
Sx = standard deviation of x
Sy = standard deviation of y

                                           _              _
                 sum( i=0 to n-1, ( x[i] - x ) * ( y[i] - y ))

correlationValue = ----------------------------------------------- 

( n - 1 ) Sx * Sy

References: <CITE>Wikipedia, the free encyclopedia (2010, April 13). 

<I>Correlation and Dependence</I>.
Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Correlation#Pearson.27s_product-moment_coefficient</CITE>

</PRE>

Parameters: 

x: The first set of values to use for the calculation.
y: The second set of values to use for the calculation.

Return value: 

float64: The Pearson correlation value.

func Percentile 

func Percentile(values []float64, percentile float64) float64

func QuartileRange 

func QuartileRange(values []float64) (float64, float64)

Finds the range of the first and third quartiles of a data set, or the 25th to 75th percentile of a set of data.

@param values The set of data to find the quartile range for. @return A range containing the 25th to 75th percentiles.

func RegularRange 

func RegularRange(values []float64) (float64, float64)

Finds the range inside which all regular values fall (inclusive).

@param values The set of data to find the regular range for. @return A range outside which all other values in the data set would be 

considered outliers.

func SpearmanCorrelation 

func SpearmanCorrelation(x, y []float64) float64

Returns the Spearman rank correlation coefficient of the 2 sets of data. Each array should be the same length and contain at least 3 values.

<PRE> 

x = values in the first set
y = values in the second set
n = number of values in each set
Rx = rank array of x, ie. the new locations of each element of x if x were sorted
Ry = rank array of y, ie. the new locations of each element of y if y were sorted

                     6 * sum( i=0 to n-1, ( Rx[i] - Ry[i] )^2 )

correlationValue = 1 - -------------------------------------------- 

n * ( n^2 - 1 )

References: <CITE>Wikipedia, the free encyclopedia (2010, April 1). 

<I>Spearman's rank correlation coefficient</I>.
Retrieved April 14, 2010, from http://en.wikipedia.org/wiki/Spearman's_rank_correlation_coefficient</CITE>

<CITE>Spiegel, Murray R. (1961). Statistics, 2nd Edition (pp 376,391-393). New York.</CITE> </PRE>

@param x The first set of data to use for the calculation. @param y The second set of data to use for the calculation. @return The Spearman correlation value. Parameters: 

x: The first set of values to use for the calculation.
y: The second set of values to use for the calculation.

Return value: 

float64: The Pearson correlation value.

func StandardDeviation 

func StandardDeviation(values []float64) float64

Returns the standard deviation of a set of values.

@param values The set to find the standard deviation of. @return The standard deviation as a double.

func Sum 

func Sum(values []float64) float64

Finds the sum of a set of values. NaN values are omitted.

@param values The set of values. @return The sum of those values.

func TandemSort 

func TandemSort(arr, companion []float64)

TandemSort sorts 2 arrays. It makes one call to data.Len to determine n, and O(n*log(n)) calls to data.Less and data.Swap. The sort is not guaranteed to be stable.

func ThirdQuartile 

func ThirdQuartile(values []float64) float64

Returns the data value that is the 75th percentile of a set of data.

@param values The set of values to find the third quartile of. @return The third quartile data point.

func TripletSort 

func TripletSort(arr, companion, companion2 []float64)

TripletSort sorts 2 arrays. It makes one call to data.Len to determine n, and O(n*log(n)) calls to data.Less and data.Swap. The sort is not guaranteed to be stable.

func WeightedMean 

func WeightedMean(values, weights []float64) float64

Finds the weighted mean of a set of values. NaN values are omitted.

@param values The set of values. @param weights The weight for each value @return The mean of those values.

Types

type Doublet 

type Doublet struct {
	Data      []float64
	Companion []float64
}

func (Doublet) Len 

func (p Doublet) Len() int

func (Doublet) Less 

func (p Doublet) Less(i, j int) bool

func (Doublet) Swap 

func (p Doublet) Swap(i, j int)

type Triplet 

type Triplet struct {
	Data       []float64
	Companion  []float64
	Companion2 []float64
}

func (Triplet) Len 

func (p Triplet) Len() int

func (Triplet) Less 

func (p Triplet) Less(i, j int) bool

func (Triplet) Swap 

func (p Triplet) Swap(i, j int)

Source Files

View all Source files

Jump to

Keyboard shortcuts

? : This menu
/ : Search site
f or F : Jump to
y or Y : Canonical URL
go.dev uses cookies from Google to deliver and enhance the quality of its services and to analyze traffic. Learn more.