math.stats #

fn absdev<T>(data []T) T

Measure of Dispersion / Spread Mean Absolute Deviation of the given input array Based on https://en.wikipedia.org/wiki/Average_absolute_deviation

fn absdev_mean<T>(data []T, mean T) T

Measure of Dispersion / Spread Mean Absolute Deviation of the given input array Based on https://en.wikipedia.org/wiki/Average_absolute_deviation

fn covariance<T>(data1 []T, data2 []T) T

fn covariance_mean<T>(data1 []T, data2 []T, mean1 T, mean2 T) T

Compute the covariance of a dataset using the recurrence relation

fn freq<T>(data []T, val T) int

Measure of Occurance Frequency of a given number Based on https://www.mathsisfun.com/data/frequency-distribution.html

fn geometric_mean<T>(data []T) T

Measure of Central Tendancy Geometric Mean of the given input array Based on https://www.mathsisfun.com/numbers/geometric-mean.html

fn harmonic_mean<T>(data []T) T

Measure of Central Tendancy Harmonic Mean of the given input array Based on https://www.mathsisfun.com/numbers/harmonic-mean.html

fn kurtosis<T>(data []T) T

fn kurtosis_mean_stddev<T>(data []T, mean T, sd T) T

Takes a dataset and finds the kurtosis using the fourth moment the deviations, normalized by the sd

fn lag1_autocorrelation<T>(data []T) T

fn lag1_autocorrelation_mean<T>(data []T, mean T) T

Compute the lag-1 autocorrelation of a dataset using the recurrence relation

fn max<T>(data []T) T

Maximum of the given input array

fn max_index<T>(data []T) int

Maximum of the given input array

fn mean<T>(data []T) T

Measure of Central Tendancy Mean of the given input array Based on https://www.mathsisfun.com/data/central-measures.html

fn median<T>(sorted_data []T) T

Measure of Central Tendancy Median of the given input array ( input array is assumed to be sorted ) Based on https://www.mathsisfun.com/data/central-measures.html

fn min<T>(data []T) T

Minimum of the given input array

fn min_index<T>(data []T) int

Minimum of the given input array

fn minmax<T>(data []T) (T, T)

Minimum and maximum of the given input array

fn minmax_index<T>(data []T) (int, int)

Minimum and maximum of the given input array

fn mode<T>(data []T) T

Measure of Central Tendancy Mode of the given input array Based on https://www.mathsisfun.com/data/central-measures.html

fn population_stddev<T>(data []T) T

Measure of Dispersion / Spread Population Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn population_stddev_mean<T>(data []T, mean T) T

Measure of Dispersion / Spread Population Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn population_variance<T>(data []T) T

Measure of Dispersion / Spread Population Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn population_variance_mean<T>(data []T, mean T) T

Measure of Dispersion / Spread Population Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn quantile<T>(sorted_data []T, f T) T

fn range<T>(data []T) T

Measure of Dispersion / Spread Range ( Maximum - Minimum ) of the given input array Based on https://www.mathsisfun.com/data/range.html

fn rms<T>(data []T) T

Root Mean Square of the given input array Based on https://en.wikipedia.org/wiki/Root_mean_square

fn sample_stddev<T>(data []T) T

Measure of Dispersion / Spread Sample Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn sample_stddev_mean<T>(data []T, mean T) T

Measure of Dispersion / Spread Sample Standard Deviation of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn sample_variance<T>(data []T) T

Measure of Dispersion / Spread Sample Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn sample_variance_mean<T>(data []T, mean T) T

Measure of Dispersion / Spread Sample Variance of the given input array Based on https://www.mathsisfun.com/data/standard-deviation.html

fn skew<T>(data []T) T

fn skew_mean_stddev<T>(data []T, mean T, sd T) T

fn tss<T>(data []T) T

Sum of squares

fn tss_mean<T>(data []T, mean T) T

Sum of squares about the mean