39 KiB
stats
import "github.com/montanaflynn/stats"
Overview
Package stats is a well tested and comprehensive statistics library package with no dependencies.
Example Usage:
// start with some source data to use
data := []float64{1.0, 2.1, 3.2, 4.823, 4.1, 5.8}
// you could also use different types like this
// data := stats.LoadRawData([]int{1, 2, 3, 4, 5})
// data := stats.LoadRawData([]interface{}{1.1, "2", 3})
// etc...
median, _ := stats.Median(data)
fmt.Println(median) // 3.65
roundedMedian, _ := stats.Round(median, 0)
fmt.Println(roundedMedian) // 4
MIT License Copyright (c) 2014-2020 Montana Flynn (https://montanaflynn.com)
Index
- Variables
- func AutoCorrelation(data Float64Data, lags int) (float64, error)
- func ChebyshevDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
- func Correlation(data1, data2 Float64Data) (float64, error)
- func Covariance(data1, data2 Float64Data) (float64, error)
- func CovariancePopulation(data1, data2 Float64Data) (float64, error)
- func CumulativeSum(input Float64Data) ([]float64, error)
- func Entropy(input Float64Data) (float64, error)
- func EuclideanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
- func GeometricMean(input Float64Data) (float64, error)
- func HarmonicMean(input Float64Data) (float64, error)
- func InterQuartileRange(input Float64Data) (float64, error)
- func ManhattanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
- func Max(input Float64Data) (max float64, err error)
- func Mean(input Float64Data) (float64, error)
- func Median(input Float64Data) (median float64, err error)
- func MedianAbsoluteDeviation(input Float64Data) (mad float64, err error)
- func MedianAbsoluteDeviationPopulation(input Float64Data) (mad float64, err error)
- func Midhinge(input Float64Data) (float64, error)
- func Min(input Float64Data) (min float64, err error)
- func MinkowskiDistance(dataPointX, dataPointY Float64Data, lambda float64) (distance float64, err error)
- func Mode(input Float64Data) (mode []float64, err error)
- func Ncr(n, r int) int
- func NormBoxMullerRvs(loc float64, scale float64, size int) []float64
- func NormCdf(x float64, loc float64, scale float64) float64
- func NormEntropy(loc float64, scale float64) float64
- func NormFit(data []float64) [2]float64
- func NormInterval(alpha float64, loc float64, scale float64) [2]float64
- func NormIsf(p float64, loc float64, scale float64) (x float64)
- func NormLogCdf(x float64, loc float64, scale float64) float64
- func NormLogPdf(x float64, loc float64, scale float64) float64
- func NormLogSf(x float64, loc float64, scale float64) float64
- func NormMean(loc float64, scale float64) float64
- func NormMedian(loc float64, scale float64) float64
- func NormMoment(n int, loc float64, scale float64) float64
- func NormPdf(x float64, loc float64, scale float64) float64
- func NormPpf(p float64, loc float64, scale float64) (x float64)
- func NormPpfRvs(loc float64, scale float64, size int) []float64
- func NormSf(x float64, loc float64, scale float64) float64
- func NormStats(loc float64, scale float64, moments string) []float64
- func NormStd(loc float64, scale float64) float64
- func NormVar(loc float64, scale float64) float64
- func Pearson(data1, data2 Float64Data) (float64, error)
- func Percentile(input Float64Data, percent float64) (percentile float64, err error)
- func PercentileNearestRank(input Float64Data, percent float64) (percentile float64, err error)
- func PopulationVariance(input Float64Data) (pvar float64, err error)
- func Round(input float64, places int) (rounded float64, err error)
- func Sample(input Float64Data, takenum int, replacement bool) ([]float64, error)
- func SampleVariance(input Float64Data) (svar float64, err error)
- func Sigmoid(input Float64Data) ([]float64, error)
- func SoftMax(input Float64Data) ([]float64, error)
- func StableSample(input Float64Data, takenum int) ([]float64, error)
- func StandardDeviation(input Float64Data) (sdev float64, err error)
- func StandardDeviationPopulation(input Float64Data) (sdev float64, err error)
- func StandardDeviationSample(input Float64Data) (sdev float64, err error)
- func StdDevP(input Float64Data) (sdev float64, err error)
- func StdDevS(input Float64Data) (sdev float64, err error)
- func Sum(input Float64Data) (sum float64, err error)
- func Trimean(input Float64Data) (float64, error)
- func VarP(input Float64Data) (sdev float64, err error)
- func VarS(input Float64Data) (sdev float64, err error)
- func Variance(input Float64Data) (sdev float64, err error)
- type Coordinate
- type Float64Data
- func LoadRawData(raw interface{}) (f Float64Data)
- func (f Float64Data) AutoCorrelation(lags int) (float64, error)
- func (f Float64Data) Correlation(d Float64Data) (float64, error)
- func (f Float64Data) Covariance(d Float64Data) (float64, error)
- func (f Float64Data) CovariancePopulation(d Float64Data) (float64, error)
- func (f Float64Data) CumulativeSum() ([]float64, error)
- func (f Float64Data) Entropy() (float64, error)
- func (f Float64Data) GeometricMean() (float64, error)
- func (f Float64Data) Get(i int) float64
- func (f Float64Data) HarmonicMean() (float64, error)
- func (f Float64Data) InterQuartileRange() (float64, error)
- func (f Float64Data) Len() int
- func (f Float64Data) Less(i, j int) bool
- func (f Float64Data) Max() (float64, error)
- func (f Float64Data) Mean() (float64, error)
- func (f Float64Data) Median() (float64, error)
- func (f Float64Data) MedianAbsoluteDeviation() (float64, error)
- func (f Float64Data) MedianAbsoluteDeviationPopulation() (float64, error)
- func (f Float64Data) Midhinge(d Float64Data) (float64, error)
- func (f Float64Data) Min() (float64, error)
- func (f Float64Data) Mode() ([]float64, error)
- func (f Float64Data) Pearson(d Float64Data) (float64, error)
- func (f Float64Data) Percentile(p float64) (float64, error)
- func (f Float64Data) PercentileNearestRank(p float64) (float64, error)
- func (f Float64Data) PopulationVariance() (float64, error)
- func (f Float64Data) Quartile(d Float64Data) (Quartiles, error)
- func (f Float64Data) QuartileOutliers() (Outliers, error)
- func (f Float64Data) Quartiles() (Quartiles, error)
- func (f Float64Data) Sample(n int, r bool) ([]float64, error)
- func (f Float64Data) SampleVariance() (float64, error)
- func (f Float64Data) Sigmoid() ([]float64, error)
- func (f Float64Data) SoftMax() ([]float64, error)
- func (f Float64Data) StandardDeviation() (float64, error)
- func (f Float64Data) StandardDeviationPopulation() (float64, error)
- func (f Float64Data) StandardDeviationSample() (float64, error)
- func (f Float64Data) Sum() (float64, error)
- func (f Float64Data) Swap(i, j int)
- func (f Float64Data) Trimean(d Float64Data) (float64, error)
- func (f Float64Data) Variance() (float64, error)
- type Outliers
- type Quartiles
- type Series
Examples
- AutoCorrelation
- ChebyshevDistance
- Correlation
- CumulativeSum
- Entropy
- LinearRegression
- LoadRawData
- Max
- Median
- Min
- Round
- Sigmoid
- SoftMax
- Sum
Package files
correlation.go cumulative_sum.go data.go deviation.go distances.go doc.go entropy.go errors.go legacy.go load.go max.go mean.go median.go min.go mode.go norm.go outlier.go percentile.go quartile.go ranksum.go regression.go round.go sample.go sigmoid.go softmax.go sum.go util.go variance.go
Variables
var (
// ErrEmptyInput Input must not be empty
ErrEmptyInput = statsError{"Input must not be empty."}
// ErrNaN Not a number
ErrNaN = statsError{"Not a number."}
// ErrNegative Must not contain negative values
ErrNegative = statsError{"Must not contain negative values."}
// ErrZero Must not contain zero values
ErrZero = statsError{"Must not contain zero values."}
// ErrBounds Input is outside of range
ErrBounds = statsError{"Input is outside of range."}
// ErrSize Must be the same length
ErrSize = statsError{"Must be the same length."}
// ErrInfValue Value is infinite
ErrInfValue = statsError{"Value is infinite."}
// ErrYCoord Y Value must be greater than zero
ErrYCoord = statsError{"Y Value must be greater than zero."}
)
These are the package-wide error values. All error identification should use these values. https://github.com/golang/go/wiki/Errors#naming
var (
EmptyInputErr = ErrEmptyInput
NaNErr = ErrNaN
NegativeErr = ErrNegative
ZeroErr = ErrZero
BoundsErr = ErrBounds
SizeErr = ErrSize
InfValue = ErrInfValue
YCoordErr = ErrYCoord
EmptyInput = ErrEmptyInput
)
Legacy error names that didn't start with Err
func AutoCorrelation
func AutoCorrelation(data Float64Data, lags int) (float64, error)
AutoCorrelation is the correlation of a signal with a delayed copy of itself as a function of delay
func ChebyshevDistance
func ChebyshevDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
ChebyshevDistance computes the Chebyshev distance between two data sets
func Correlation
func Correlation(data1, data2 Float64Data) (float64, error)
Correlation describes the degree of relationship between two sets of data
func Covariance
func Covariance(data1, data2 Float64Data) (float64, error)
Covariance is a measure of how much two sets of data change
func CovariancePopulation
func CovariancePopulation(data1, data2 Float64Data) (float64, error)
CovariancePopulation computes covariance for entire population between two variables.
func CumulativeSum
func CumulativeSum(input Float64Data) ([]float64, error)
CumulativeSum calculates the cumulative sum of the input slice
func Entropy
func Entropy(input Float64Data) (float64, error)
Entropy provides calculation of the entropy
func EuclideanDistance
func EuclideanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
EuclideanDistance computes the Euclidean distance between two data sets
func GeometricMean
func GeometricMean(input Float64Data) (float64, error)
GeometricMean gets the geometric mean for a slice of numbers
func HarmonicMean
func HarmonicMean(input Float64Data) (float64, error)
HarmonicMean gets the harmonic mean for a slice of numbers
func InterQuartileRange
func InterQuartileRange(input Float64Data) (float64, error)
InterQuartileRange finds the range between Q1 and Q3
func ManhattanDistance
func ManhattanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error)
ManhattanDistance computes the Manhattan distance between two data sets
func Max
func Max(input Float64Data) (max float64, err error)
Max finds the highest number in a slice
func Mean
func Mean(input Float64Data) (float64, error)
Mean gets the average of a slice of numbers
func Median
func Median(input Float64Data) (median float64, err error)
Median gets the median number in a slice of numbers
func MedianAbsoluteDeviation
func MedianAbsoluteDeviation(input Float64Data) (mad float64, err error)
MedianAbsoluteDeviation finds the median of the absolute deviations from the dataset median
func MedianAbsoluteDeviationPopulation
func MedianAbsoluteDeviationPopulation(input Float64Data) (mad float64, err error)
MedianAbsoluteDeviationPopulation finds the median of the absolute deviations from the population median
func Midhinge
func Midhinge(input Float64Data) (float64, error)
Midhinge finds the average of the first and third quartiles
func Min
func Min(input Float64Data) (min float64, err error)
Min finds the lowest number in a set of data
func MinkowskiDistance
func MinkowskiDistance(dataPointX, dataPointY Float64Data, lambda float64) (distance float64, err error)
MinkowskiDistance computes the Minkowski distance between two data sets
Arguments:
dataPointX: First set of data points
dataPointY: Second set of data points. Length of both data
sets must be equal.
lambda: aka p or city blocks; With lambda = 1
returned distance is manhattan distance and
lambda = 2; it is euclidean distance. Lambda
reaching to infinite - distance would be chebysev
distance.
Return:
Distance or error
func Mode
func Mode(input Float64Data) (mode []float64, err error)
Mode gets the mode [most frequent value(s)] of a slice of float64s
func Ncr
func Ncr(n, r int) int
Ncr is an N choose R algorithm. Aaron Cannon's algorithm.
func NormBoxMullerRvs
func NormBoxMullerRvs(loc float64, scale float64, size int) []float64
NormBoxMullerRvs generates random variates using the Box–Muller transform. For more information please visit: http://mathworld.wolfram.com/Box-MullerTransformation.html
func NormCdf
func NormCdf(x float64, loc float64, scale float64) float64
NormCdf is the cumulative distribution function.
func NormEntropy
func NormEntropy(loc float64, scale float64) float64
NormEntropy is the differential entropy of the RV.
func NormFit
func NormFit(data []float64) [2]float64
NormFit returns the maximum likelihood estimators for the Normal Distribution. Takes array of float64 values. Returns array of Mean followed by Standard Deviation.
func NormInterval
func NormInterval(alpha float64, loc float64, scale float64) [2]float64
NormInterval finds endpoints of the range that contains alpha percent of the distribution.
func NormIsf
func NormIsf(p float64, loc float64, scale float64) (x float64)
NormIsf is the inverse survival function (inverse of sf).
func NormLogCdf
func NormLogCdf(x float64, loc float64, scale float64) float64
NormLogCdf is the log of the cumulative distribution function.
func NormLogPdf
func NormLogPdf(x float64, loc float64, scale float64) float64
NormLogPdf is the log of the probability density function.
func NormLogSf
func NormLogSf(x float64, loc float64, scale float64) float64
NormLogSf is the log of the survival function.
func NormMean
func NormMean(loc float64, scale float64) float64
NormMean is the mean/expected value of the distribution.
func NormMedian
func NormMedian(loc float64, scale float64) float64
NormMedian is the median of the distribution.
func NormMoment
func NormMoment(n int, loc float64, scale float64) float64
NormMoment approximates the non-central (raw) moment of order n. For more information please visit: https://math.stackexchange.com/questions/1945448/methods-for-finding-raw-moments-of-the-normal-distribution
func NormPdf
func NormPdf(x float64, loc float64, scale float64) float64
NormPdf is the probability density function.
func NormPpf
func NormPpf(p float64, loc float64, scale float64) (x float64)
NormPpf is the point percentile function. This is based on Peter John Acklam's inverse normal CDF. algorithm: http://home.online.no/~pjacklam/notes/invnorm/ (no longer visible). For more information please visit: https://stackedboxes.org/2017/05/01/acklams-normal-quantile-function/
func NormPpfRvs
func NormPpfRvs(loc float64, scale float64, size int) []float64
NormPpfRvs generates random variates using the Point Percentile Function. For more information please visit: https://demonstrations.wolfram.com/TheMethodOfInverseTransforms/
func NormSf
func NormSf(x float64, loc float64, scale float64) float64
NormSf is the survival function (also defined as 1 - cdf, but sf is sometimes more accurate).
func NormStats
func NormStats(loc float64, scale float64, moments string) []float64
NormStats returns the mean, variance, skew, and/or kurtosis. Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). Takes string containing any of 'mvsk'. Returns array of m v s k in that order.
func NormStd
func NormStd(loc float64, scale float64) float64
NormStd is the standard deviation of the distribution.
func NormVar
func NormVar(loc float64, scale float64) float64
NormVar is the variance of the distribution.
func Pearson
func Pearson(data1, data2 Float64Data) (float64, error)
Pearson calculates the Pearson product-moment correlation coefficient between two variables
func Percentile
func Percentile(input Float64Data, percent float64) (percentile float64, err error)
Percentile finds the relative standing in a slice of floats
func PercentileNearestRank
func PercentileNearestRank(input Float64Data, percent float64) (percentile float64, err error)
PercentileNearestRank finds the relative standing in a slice of floats using the Nearest Rank method
func PopulationVariance
func PopulationVariance(input Float64Data) (pvar float64, err error)
PopulationVariance finds the amount of variance within a population
func Round
func Round(input float64, places int) (rounded float64, err error)
Round a float to a specific decimal place or precision
func Sample
func Sample(input Float64Data, takenum int, replacement bool) ([]float64, error)
Sample returns sample from input with replacement or without
func SampleVariance
func SampleVariance(input Float64Data) (svar float64, err error)
SampleVariance finds the amount of variance within a sample
func Sigmoid
func Sigmoid(input Float64Data) ([]float64, error)
Sigmoid returns the input values in the range of -1 to 1 along the sigmoid or s-shaped curve, commonly used in machine learning while training neural networks as an activation function.
func SoftMax
func SoftMax(input Float64Data) ([]float64, error)
SoftMax returns the input values in the range of 0 to 1 with sum of all the probabilities being equal to one. It is commonly used in machine learning neural networks.
func StableSample
func StableSample(input Float64Data, takenum int) ([]float64, error)
StableSample like stable sort, it returns samples from input while keeps the order of original data.
func StandardDeviation
func StandardDeviation(input Float64Data) (sdev float64, err error)
StandardDeviation the amount of variation in the dataset
func StandardDeviationPopulation
func StandardDeviationPopulation(input Float64Data) (sdev float64, err error)
StandardDeviationPopulation finds the amount of variation from the population
func StandardDeviationSample
func StandardDeviationSample(input Float64Data) (sdev float64, err error)
StandardDeviationSample finds the amount of variation from a sample
func StdDevP
func StdDevP(input Float64Data) (sdev float64, err error)
StdDevP is a shortcut to StandardDeviationPopulation
func StdDevS
func StdDevS(input Float64Data) (sdev float64, err error)
StdDevS is a shortcut to StandardDeviationSample
func Sum
func Sum(input Float64Data) (sum float64, err error)
Sum adds all the numbers of a slice together
func Trimean
func Trimean(input Float64Data) (float64, error)
Trimean finds the average of the median and the midhinge
func VarP
func VarP(input Float64Data) (sdev float64, err error)
VarP is a shortcut to PopulationVariance
func VarS
func VarS(input Float64Data) (sdev float64, err error)
VarS is a shortcut to SampleVariance
func Variance
func Variance(input Float64Data) (sdev float64, err error)
Variance the amount of variation in the dataset
type Coordinate
type Coordinate struct {
X, Y float64
}
Coordinate holds the data in a series
func ExpReg
func ExpReg(s []Coordinate) (regressions []Coordinate, err error)
ExpReg is a shortcut to ExponentialRegression
func LinReg
func LinReg(s []Coordinate) (regressions []Coordinate, err error)
LinReg is a shortcut to LinearRegression
func LogReg
func LogReg(s []Coordinate) (regressions []Coordinate, err error)
LogReg is a shortcut to LogarithmicRegression
type Float64Data
type Float64Data []float64
Float64Data is a named type for []float64 with helper methods
func LoadRawData
func LoadRawData(raw interface{}) (f Float64Data)
LoadRawData parses and converts a slice of mixed data types to floats
func (Float64Data) AutoCorrelation
func (f Float64Data) AutoCorrelation(lags int) (float64, error)
AutoCorrelation is the correlation of a signal with a delayed copy of itself as a function of delay
func (Float64Data) Correlation
func (f Float64Data) Correlation(d Float64Data) (float64, error)
Correlation describes the degree of relationship between two sets of data
func (Float64Data) Covariance
func (f Float64Data) Covariance(d Float64Data) (float64, error)
Covariance is a measure of how much two sets of data change
func (Float64Data) CovariancePopulation
func (f Float64Data) CovariancePopulation(d Float64Data) (float64, error)
CovariancePopulation computes covariance for entire population between two variables
func (Float64Data) CumulativeSum
func (f Float64Data) CumulativeSum() ([]float64, error)
CumulativeSum returns the cumulative sum of the data
func (Float64Data) Entropy
func (f Float64Data) Entropy() (float64, error)
Entropy provides calculation of the entropy
func (Float64Data) GeometricMean
func (f Float64Data) GeometricMean() (float64, error)
GeometricMean returns the median of the data
func (Float64Data) Get
func (f Float64Data) Get(i int) float64
Get item in slice
func (Float64Data) HarmonicMean
func (f Float64Data) HarmonicMean() (float64, error)
HarmonicMean returns the mode of the data
func (Float64Data) InterQuartileRange
func (f Float64Data) InterQuartileRange() (float64, error)
InterQuartileRange finds the range between Q1 and Q3
func (Float64Data) Len
func (f Float64Data) Len() int
Len returns length of slice
func (Float64Data) Less
func (f Float64Data) Less(i, j int) bool
Less returns if one number is less than another
func (Float64Data) Max
func (f Float64Data) Max() (float64, error)
Max returns the maximum number in the data
func (Float64Data) Mean
func (f Float64Data) Mean() (float64, error)
Mean returns the mean of the data
func (Float64Data) Median
func (f Float64Data) Median() (float64, error)
Median returns the median of the data
func (Float64Data) MedianAbsoluteDeviation
func (f Float64Data) MedianAbsoluteDeviation() (float64, error)
MedianAbsoluteDeviation the median of the absolute deviations from the dataset median
func (Float64Data) MedianAbsoluteDeviationPopulation
func (f Float64Data) MedianAbsoluteDeviationPopulation() (float64, error)
MedianAbsoluteDeviationPopulation finds the median of the absolute deviations from the population median
func (Float64Data) Midhinge
func (f Float64Data) Midhinge(d Float64Data) (float64, error)
Midhinge finds the average of the first and third quartiles
func (Float64Data) Min
func (f Float64Data) Min() (float64, error)
Min returns the minimum number in the data
func (Float64Data) Mode
func (f Float64Data) Mode() ([]float64, error)
Mode returns the mode of the data
func (Float64Data) Pearson
func (f Float64Data) Pearson(d Float64Data) (float64, error)
Pearson calculates the Pearson product-moment correlation coefficient between two variables.
func (Float64Data) Percentile
func (f Float64Data) Percentile(p float64) (float64, error)
Percentile finds the relative standing in a slice of floats
func (Float64Data) PercentileNearestRank
func (f Float64Data) PercentileNearestRank(p float64) (float64, error)
PercentileNearestRank finds the relative standing using the Nearest Rank method
func (Float64Data) PopulationVariance
func (f Float64Data) PopulationVariance() (float64, error)
PopulationVariance finds the amount of variance within a population
func (Float64Data) Quartile
func (f Float64Data) Quartile(d Float64Data) (Quartiles, error)
Quartile returns the three quartile points from a slice of data
func (Float64Data) QuartileOutliers
func (f Float64Data) QuartileOutliers() (Outliers, error)
QuartileOutliers finds the mild and extreme outliers
func (Float64Data) Quartiles
func (f Float64Data) Quartiles() (Quartiles, error)
Quartiles returns the three quartile points from instance of Float64Data
func (Float64Data) Sample
func (f Float64Data) Sample(n int, r bool) ([]float64, error)
Sample returns sample from input with replacement or without
func (Float64Data) SampleVariance
func (f Float64Data) SampleVariance() (float64, error)
SampleVariance finds the amount of variance within a sample
func (Float64Data) Sigmoid
func (f Float64Data) Sigmoid() ([]float64, error)
Sigmoid returns the input values along the sigmoid or s-shaped curve
func (Float64Data) SoftMax
func (f Float64Data) SoftMax() ([]float64, error)
SoftMax returns the input values in the range of 0 to 1 with sum of all the probabilities being equal to one.
func (Float64Data) StandardDeviation
func (f Float64Data) StandardDeviation() (float64, error)
StandardDeviation the amount of variation in the dataset
func (Float64Data) StandardDeviationPopulation
func (f Float64Data) StandardDeviationPopulation() (float64, error)
StandardDeviationPopulation finds the amount of variation from the population
func (Float64Data) StandardDeviationSample
func (f Float64Data) StandardDeviationSample() (float64, error)
StandardDeviationSample finds the amount of variation from a sample
func (Float64Data) Sum
func (f Float64Data) Sum() (float64, error)
Sum returns the total of all the numbers in the data
func (Float64Data) Swap
func (f Float64Data) Swap(i, j int)
Swap switches out two numbers in slice
func (Float64Data) Trimean
func (f Float64Data) Trimean(d Float64Data) (float64, error)
Trimean finds the average of the median and the midhinge
func (Float64Data) Variance
func (f Float64Data) Variance() (float64, error)
Variance the amount of variation in the dataset
type Outliers
type Outliers struct {
Mild Float64Data
Extreme Float64Data
}
Outliers holds mild and extreme outliers found in data
func QuartileOutliers
func QuartileOutliers(input Float64Data) (Outliers, error)
QuartileOutliers finds the mild and extreme outliers
type Quartiles
type Quartiles struct {
Q1 float64
Q2 float64
Q3 float64
}
Quartiles holds the three quartile points
func Quartile
func Quartile(input Float64Data) (Quartiles, error)
Quartile returns the three quartile points from a slice of data
type Series
type Series []Coordinate
Series is a container for a series of data
func ExponentialRegression
func ExponentialRegression(s Series) (regressions Series, err error)
ExponentialRegression returns an exponential regression on data series
func LinearRegression
func LinearRegression(s Series) (regressions Series, err error)
LinearRegression finds the least squares linear regression on data series
func LogarithmicRegression
func LogarithmicRegression(s Series) (regressions Series, err error)
LogarithmicRegression returns an logarithmic regression on data series
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