statistics

Documentation

Index

• Variables
• func LeastSquares(xs, ys []float64) (m, b float64, err error)
• func Mean(series []float64) float64
• type Predictor

Variables

var (
	ErrUnequalArrays    = errors.New("coordinate arrays are of different lengths")
	ErrInsufficientData = errors.New("not enough data to make a prediction")
)

var (
	// LeastSquaresPredictor uses the ordinary least squares method of
	// estimation to predict future values
	LeastSquaresPredictor = &olsPredictor{}
)

Functions

func LeastSquares

func LeastSquares(xs, ys []float64) (m, b float64, err error)

LeastSquares calculates the slope and y-intercept of the line of best fit for the series of points represented as arrays of x- and y-coordinates using the Ordinary Least Squares method.

func Mean

func Mean(series []float64) float64

Mean calculates the mean of an array of floats

Types

type Predictor

type Predictor interface {
	// Predict uses the timestamp/value pairs passed in to predict the value at
	// time now+period
	Predict(period time.Duration, timestamps, values []float64) (float64, error)
}

Predictor represents a strategy for predicting a future value based on historic values