stats #
fn absdev #
fn absdev[T](t &vtl.Tensor[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 #
fn absdev_mean[T](t &vtl.Tensor[T], provided_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 #
fn covariance[T](a &vtl.Tensor[T], b &vtl.Tensor[T]) T
fn covariance_mean #
fn covariance_mean[T](a &vtl.Tensor[T], b &vtl.Tensor[T], mean1 T, mean2 T) T
Compute the covariance of a dataset using the recurrence relation
fn freq #
fn freq[T](t &vtl.Tensor[T], val T) int
Measure of Occurrence Frequency of a given number Based on https://www.mathsisfun.com/data/frequency-distribution.html
fn geometric_mean #
fn geometric_mean[T](t &vtl.Tensor[T]) T
Measure of Central Tendency Geometric Mean of the given input array Based on https://www.mathsisfun.com/numbers/geometric-mean.html
fn harmonic_mean #
fn harmonic_mean[T](t &vtl.Tensor[T]) T
Measure of Central Tendency Harmonic Mean of the given input array Based on https://www.mathsisfun.com/numbers/harmonic-mean.html
fn kurtosis #
fn kurtosis[T](t &vtl.Tensor[T]) T
fn kurtosis_mean_stddev #
fn kurtosis_mean_stddev[T](t &vtl.Tensor[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 #
fn lag1_autocorrelation[T](t &vtl.Tensor[T]) T
fn lag1_autocorrelation_mean #
fn lag1_autocorrelation_mean[T](t &vtl.Tensor[T], provided_mean T) T
Compute the lag-1 autocorrelation of a dataset using the recurrence relation
fn max #
fn max[T](t &vtl.Tensor[T]) T
Maximum of the given input array
fn max_index #
fn max_index[T](t &vtl.Tensor[T]) int
Maximum of the given input array
fn mean #
fn mean[T](t &vtl.Tensor[T]) T
Measure of Central Tendency Mean of the given input array Based on https://www.mathsisfun.com/data/central-measures.html
fn median #
fn median[T](t &vtl.Tensor[T]) T
Measure of Central Tendency 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 #
fn min[T](t &vtl.Tensor[T]) T
Minimum of the given input array
fn min_index #
fn min_index[T](t &vtl.Tensor[T]) int
Minimum of the given input array
fn minmax #
fn minmax[T](t &vtl.Tensor[T]) (T, T)
Minimum and maximum of the given input array
fn minmax_index #
fn minmax_index[T](t &vtl.Tensor[T]) (int, int)
Minimum and maximum of the given input array
fn mode #
fn mode[T](t &vtl.Tensor[T]) T
Measure of Central Tendency Mode of the given input array Based on https://www.mathsisfun.com/data/central-measures.html
fn population_stddev #
fn population_stddev[T](t &vtl.Tensor[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 #
fn population_stddev_mean[T](t &vtl.Tensor[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 #
fn population_variance[T](t &vtl.Tensor[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 #
fn population_variance_mean[T](t &vtl.Tensor[T], provided_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 prod #
fn prod[T](t &vtl.Tensor[T]) T
prod returns the product of all elements of the given tensor
fn prod_axis #
fn prod_axis[T](t &vtl.Tensor[T], data AxisData) T
prod_axis_dims returns the product of a given Tensor along a provided axis with the reduced dimension intact
fn prod_axis_with_dims #
fn prod_axis_with_dims[T](t &vtl.Tensor[T], data AxisData) T
prod_axis_dims returns the product of a Tensor along a provided axis with the reduced dimension intact
fn quantile #
fn quantile[T](sorted_t &vtl.Tensor[T], f T) T
fn range #
fn range[T](t &vtl.Tensor[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 #
fn rms[T](t &vtl.Tensor[T]) T
Root Mean Square of the given input array Based on https://en.wikipedia.org/wiki/Root_mean_square
fn sample_stddev #
fn sample_stddev[T](t &vtl.Tensor[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 #
fn sample_stddev_mean[T](t &vtl.Tensor[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 #
fn sample_variance[T](t &vtl.Tensor[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 #
fn sample_variance_mean[T](t &vtl.Tensor[T], provided_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 #
fn skew[T](t &vtl.Tensor[T]) T
fn skew_mean_stddev #
fn skew_mean_stddev[T](t &vtl.Tensor[T], mean T, sd T) T
fn sum #
fn sum[T](t &vtl.Tensor[T]) T
sum returns the sum of all elements of the given tensor
fn sum_axis #
fn sum_axis[T](t &vtl.Tensor[T], data AxisData) T
sum_axis returns the sum of a given Tensor along a provided axis
fn sum_axis_with_dims #
fn sum_axis_with_dims[T](t &vtl.Tensor[T], data AxisData) T
sum_axis_dims returns the sum of a given Tensor along a provided axis with the reduced dimension intact
fn tss #
fn tss[T](t &vtl.Tensor[T]) T
Sum of squares
fn tss_mean #
fn tss_mean[T](t &vtl.Tensor[T], provided_mean T) T
Sum of squares about the mean
struct AxisData #
struct AxisData {
pub:
axis int
}
- fn absdev
- fn absdev_mean
- fn covariance
- fn covariance_mean
- fn freq
- fn geometric_mean
- fn harmonic_mean
- fn kurtosis
- fn kurtosis_mean_stddev
- fn lag1_autocorrelation
- fn lag1_autocorrelation_mean
- fn max
- fn max_index
- fn mean
- fn median
- fn min
- fn min_index
- fn minmax
- fn minmax_index
- fn mode
- fn population_stddev
- fn population_stddev_mean
- fn population_variance
- fn population_variance_mean
- fn prod
- fn prod_axis
- fn prod_axis_with_dims
- fn quantile
- fn range
- fn rms
- fn sample_stddev
- fn sample_stddev_mean
- fn sample_variance
- fn sample_variance_mean
- fn skew
- fn skew_mean_stddev
- fn sum
- fn sum_axis
- fn sum_axis_with_dims
- fn tss
- fn tss_mean
- struct AxisData