Versions in this module Expand all Collapse all v0 v0.6.5 Feb 5, 2020 v0.6.3 Feb 5, 2020 Changes in this version + func Bhattacharyya(p, q []float64) float64 + func BivariateMoment(r, s float64, x, y, weights []float64) float64 + func CDF(q float64, c CumulantKind, x, weights []float64) float64 + func ChiSquare(obs, exp []float64) float64 + func CircularMean(x, weights []float64) float64 + func Correlation(x, y, weights []float64) float64 + func CorrelationMatrix(dst *mat.SymDense, x mat.Matrix, weights []float64) + func Covariance(x, y, weights []float64) float64 + func CovarianceMatrix(dst *mat.SymDense, x mat.Matrix, weights []float64) + func CrossEntropy(p, q []float64) float64 + func Entropy(p []float64) float64 + func ExKurtosis(x, weights []float64) float64 + func GeometricMean(x, weights []float64) float64 + func HarmonicMean(x, weights []float64) float64 + func Hellinger(p, q []float64) float64 + func Histogram(count, dividers, x, weights []float64) []float64 + func JensenShannon(p, q []float64) float64 + func Kendall(x, y, weights []float64) float64 + func KolmogorovSmirnov(x, xWeights, y, yWeights []float64) float64 + func KullbackLeibler(p, q []float64) float64 + func LinearRegression(x, y, weights []float64, origin bool) (alpha, beta float64) + func Mahalanobis(x, y mat.Vector, chol *mat.Cholesky) float64 + func Mean(x, weights []float64) float64 + func MeanStdDev(x, weights []float64) (mean, std float64) + func MeanVariance(x, weights []float64) (mean, variance float64) + func Mode(x, weights []float64) (val float64, count float64) + func Moment(moment float64, x, weights []float64) float64 + func MomentAbout(moment float64, x []float64, mean float64, weights []float64) float64 + func Quantile(p float64, c CumulantKind, x, weights []float64) float64 + func RNoughtSquared(x, y, weights []float64, beta float64) float64 + func ROC(cutoffs, y []float64, classes []bool, weights []float64) (tpr, fpr, thresh []float64) + func RSquared(x, y, weights []float64, alpha, beta float64) float64 + func RSquaredFrom(estimates, values, weights []float64) float64 + func Skew(x, weights []float64) float64 + func SortWeighted(x, weights []float64) + func SortWeightedLabeled(x []float64, labels []bool, weights []float64) + func StdDev(x, weights []float64) float64 + func StdErr(std, sampleSize float64) float64 + func StdScore(x, mean, std float64) float64 + func Variance(x, weights []float64) float64 + type CC struct + func (c *CC) CanonicalCorrelations(x, y mat.Matrix, weights []float64) error + func (c *CC) CorrsTo(dst []float64) []float64 + func (c *CC) LeftTo(dst *mat.Dense, spheredSpace bool) + func (c *CC) RightTo(dst *mat.Dense, spheredSpace bool) + type CumulantKind int + const Empirical + const LinInterp + type PC struct + func (c *PC) PrincipalComponents(a mat.Matrix, weights []float64) (ok bool) + func (c *PC) VarsTo(dst []float64) []float64 + func (c *PC) VectorsTo(dst *mat.Dense)
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