Documentation
¶
Index ¶
- func Abs(series []float64) ([]float64, error)
- func AutoCorrelation(series []float64, lags int) (float64, error)
- func Correlation(series1, series2 []float64) (float64, error)
- func Covariance(series1, series2 []float64) (float64, error)
- func CovariancePopulation(series1, series2 []float64) (float64, error)
- func CumulativeSum(series []float64) ([]float64, error)
- func EuclideanDistance(series1, series2 []float64) (float64, error)
- func InLimit(value any) bool
- func KolmogorovSmirnov(series1, series2 []float64) (float64, error)
- func Max(series []float64) (float64, error)
- func Mean(series []float64) (float64, error)
- func Min(series []float64) (float64, error)
- func MinMaxNormalize(series []float64) ([]float64, error)
- func Normalize(series []float64) ([]float64, error)
- func Prediction(source []float64, length int) []float64
- func StandardDeviation(series []float64) (float64, error)
- func Standardize(series []float64) ([]float64, error)
- func Sum(series []float64) (float64, error)
- func Variance(series []float64) (float64, error)
- type FunctionSeries
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func AutoCorrelation ¶
AutoCorrelation is the correlation of a signal with a delayed copy of itself as a function of delay.
func Correlation ¶
Correlation describes the degree of relationship between data series.
func Covariance ¶
Covariance describes the degree of relationship between data series.
func CovariancePopulation ¶
CovariancePopulation describes the degree of relationship for entire population between data series.
func CumulativeSum ¶
CumulativeSum returns the cumulative sum of the data series.
func EuclideanDistance ¶
EuclideanDistance returns the summarized Euclidean distance between two points of the data series.
func KolmogorovSmirnov ¶
KolmogorovSmirnov returns the largest distance between two empirical data series.
func MinMaxNormalize ¶
MinMaxNormalize returns the scale function of the data series.
func Prediction ¶
Prediction returns a Time Series Forecast (TSF) by building models based on historical data series.
func StandardDeviation ¶
StandardDeviation returns the standard deviation of the data series.
func Standardize ¶
Standardize returns the scale function of the data series.
Types ¶
type FunctionSeries ¶
FunctionSeries is a 1-dimensional function.
func ExponentialRegression ¶
func ExponentialRegression(series []float64) (FunctionSeries, error)
ExponentialRegression models an exponential relationship within a data set.
func LinearInterpolation ¶
func LinearInterpolation(min, max float64, points int) FunctionSeries
LinearInterpolation sets values at positions between data points.
func LinearRegression ¶
func LinearRegression(series []float64) (FunctionSeries, error)
LinearRegression models an linear relationship within a data set.
Source Files