stats

Documentation

Index

• func LinearRegression(xData, yData []float64) (slope, intercept, rsquared float64, count int, ...)
• func StatsCount(data []float64) int
• func StatsMax(data []float64) float64
• func StatsMean(data []float64) float64
• func StatsMin(data []float64) float64
• func StatsPopulationKurtosis(data []float64) (kurtosis float64)
• func StatsPopulationSkew(data []float64) (skew float64)
• func StatsPopulationStandardDeviation(data []float64) float64
• func StatsPopulationVariance(data []float64) float64
• func StatsSampleKurtosis(data []float64) float64
• func StatsSampleSkew(data []float64) float64
• func StatsSampleStandardDeviation(data []float64) float64
• func StatsSampleVariance(data []float64) float64
• func StatsSum(data []float64) (sum float64)
• type Regression
  • func (r *Regression) Count() int
  • func (r *Regression) Intercept() float64
  • func (r *Regression) InterceptStandardError() float64
  • func (r *Regression) RSquared() float64
  • func (r *Regression) Size() int
  • func (r *Regression) Slope() float64
  • func (r *Regression) SlopeStandardError() float64
  • func (r *Regression) Update(x, y float64)
  • func (r *Regression) UpdateArray(xData, yData []float64)
• type Stats
  • func (d *Stats) Count() int
  • func (d *Stats) Max() float64
  • func (d *Stats) Mean() float64
  • func (d *Stats) Min() float64
  • func (d *Stats) PopulationKurtosis() float64
  • func (d *Stats) PopulationSkew() float64
  • func (d *Stats) PopulationStandardDeviation() float64
  • func (d *Stats) PopulationVariance() float64
  • func (d *Stats) SampleKurtosis() float64
  • func (d *Stats) SampleSkew() float64
  • func (d *Stats) SampleStandardDeviation() float64
  • func (d *Stats) SampleVariance() float64
  • func (d *Stats) Size() int
  • func (d *Stats) Sum() float64
  • func (d *Stats) Update(x float64)
  • func (d *Stats) UpdateArray(data []float64)

Functions

func LinearRegression

func LinearRegression(xData, yData []float64) (slope, intercept, rsquared float64,
	count int, slopeStdErr, interceptStdErr float64)

func StatsCount

func StatsCount(data []float64) int

Batch functions

These are non-incremental functions that operate only on the data given them. They're prefixed with 'Calc'.

func StatsMax

func StatsMax(data []float64) float64

func StatsMean

func StatsMean(data []float64) float64

func StatsMin

func StatsMin(data []float64) float64

func StatsPopulationKurtosis

func StatsPopulationKurtosis(data []float64) (kurtosis float64)

The kurtosis functions return _excess_ kurtosis

func StatsPopulationSkew

func StatsPopulationSkew(data []float64) (skew float64)

func StatsPopulationStandardDeviation

func StatsPopulationStandardDeviation(data []float64) float64

func StatsPopulationVariance

func StatsPopulationVariance(data []float64) float64

func StatsSampleKurtosis

func StatsSampleKurtosis(data []float64) float64

func StatsSampleSkew

func StatsSampleSkew(data []float64) float64

func StatsSampleStandardDeviation

func StatsSampleStandardDeviation(data []float64) float64

func StatsSampleVariance

func StatsSampleVariance(data []float64) float64

func StatsSum

func StatsSum(data []float64) (sum float64)

Types

type Regression

type Regression struct {
	// contains filtered or unexported fields
}

structure to contain the accumulating regression components

func (*Regression) Count

func (r *Regression) Count() int

func (*Regression) Intercept

func (r *Regression) Intercept() float64

func (*Regression) InterceptStandardError

func (r *Regression) InterceptStandardError() float64

func (*Regression) RSquared

func (r *Regression) RSquared() float64

func (*Regression) Size

func (r *Regression) Size() int

func (*Regression) Slope

func (r *Regression) Slope() float64

func (*Regression) SlopeStandardError

func (r *Regression) SlopeStandardError() float64

func (*Regression) Update

func (r *Regression) Update(x, y float64)

Update the stats with a new point.

func (*Regression) UpdateArray

func (r *Regression) UpdateArray(xData, yData []float64)

Update the stats with arrays of x and y values.

type Stats

type Stats struct {
	// contains filtered or unexported fields
}

Data structure to contain accumulating values and moments

func (*Stats) Count

func (d *Stats) Count() int

func (*Stats) Max

func (d *Stats) Max() float64

func (*Stats) Mean

func (d *Stats) Mean() float64

func (*Stats) Min

func (d *Stats) Min() float64

func (*Stats) PopulationKurtosis

func (d *Stats) PopulationKurtosis() float64

The kurtosis functions return _excess_ kurtosis, so that the kurtosis of a normal distribution = 0.0. Then kurtosis < 0.0 indicates platykurtic (flat) while kurtosis > 0.0 indicates leptokurtic (peaked) and near 0 indicates mesokurtic.Update

func (*Stats) PopulationSkew

func (d *Stats) PopulationSkew() float64

func (*Stats) PopulationStandardDeviation

func (d *Stats) PopulationStandardDeviation() float64

func (*Stats) PopulationVariance

func (d *Stats) PopulationVariance() float64

func (*Stats) SampleKurtosis

func (d *Stats) SampleKurtosis() float64

func (*Stats) SampleSkew

func (d *Stats) SampleSkew() float64

func (*Stats) SampleStandardDeviation

func (d *Stats) SampleStandardDeviation() float64

func (*Stats) SampleVariance

func (d *Stats) SampleVariance() float64

func (*Stats) Size

func (d *Stats) Size() int

func (*Stats) Sum

func (d *Stats) Sum() float64

func (*Stats) Update

func (d *Stats) Update(x float64)

Update the stats with the given value.

func (*Stats) UpdateArray

func (d *Stats) UpdateArray(data []float64)

Update the stats with the given array of values.