Numerix v0.4.1 Numerix.Statistics

Common statistical functions.

Summary

Functions

Calculates the unbiased covariance from two sample vectors. It is a measure of how much the two vectors change together

The sharpness of the peak of a frequency-distribution curve. It defines the extent to which a distribution differs from a normal distribution. Like skewness, it describes the shape of a probability distribution

The average of a list of numbers

The middle value in a list of numbers

The most frequent value(s) in a list

The nth moment about the mean for a sample. Used to calculate skewness and kurtosis

Estimates the p-Percentile value from the vector. Approximately median-unbiased irrespective of the sample distribution. This implements the R-8 type of https://en.wikipedia.org/wiki/Quantile

Calculates the population covariance from two full population vectors. It is a measure of how much the two vectors change together

The standard deviation for a full population. It measures the amount of variation of the vector

The variance for a full population. It measures how far the vector is spread out from the mean

Estimates the tau-th quantile from the vector. Approximately median-unbiased irrespective of the sample distribution. This implements the R-8 type of https://en.wikipedia.org/wiki/Quantile

The difference between the largest and smallest values in a list

The skewness of a frequency-distribution curve. It defines the extent to which a distribution differs from a normal distribution. Like kurtosis, it describes the shape of a probability distribution

The unbiased standard deviation from a sample. It measures the amount of variation of the vector

The unbiased population variance from a sample. It measures how far the vector is spread out from the mean

Calculates the weighted measure of how much two vectors change together

Calculates the weighted average of a list of numbers

Functions

covariance(xs, ys)

Specs

covariance([number], [number]) :: Numerix.Common.maybe_float

Calculates the unbiased covariance from two sample vectors. It is a measure of how much the two vectors change together.

kurtosis(xs)

Specs

kurtosis([number]) :: Numerix.Common.maybe_float

The sharpness of the peak of a frequency-distribution curve. It defines the extent to which a distribution differs from a normal distribution. Like skewness, it describes the shape of a probability distribution.

mean(xs)

Specs

mean([number]) :: Numerix.Common.maybe_float

The average of a list of numbers.

median(xs)

Specs

median([number]) :: Numerix.Common.maybe_float

The middle value in a list of numbers.

mode(xs)

Specs

mode([number]) :: [number] | nil

The most frequent value(s) in a list.

moment(xs, n)

Specs

moment([number], pos_integer) :: Numerix.Common.maybe_float

The nth moment about the mean for a sample. Used to calculate skewness and kurtosis.

percentile(xs, p)

Specs

percentile([number], integer) :: Numerix.Common.maybe_float

Estimates the p-Percentile value from the vector. Approximately median-unbiased irrespective of the sample distribution. This implements the R-8 type of https://en.wikipedia.org/wiki/Quantile.

population_covariance(xs, ys)

Specs

population_covariance([number], [number]) :: Numerix.Common.maybe_float

Calculates the population covariance from two full population vectors. It is a measure of how much the two vectors change together.

population_std_dev(xs)

Specs

population_std_dev([number]) :: Numerix.Common.maybe_float

The standard deviation for a full population. It measures the amount of variation of the vector.

population_variance(xs)

Specs

population_variance([number]) :: Numerix.Common.maybe_float

The variance for a full population. It measures how far the vector is spread out from the mean.

quantile(xs, tau)

Specs

quantile([number], number) :: Numerix.Common.maybe_float

Estimates the tau-th quantile from the vector. Approximately median-unbiased irrespective of the sample distribution. This implements the R-8 type of https://en.wikipedia.org/wiki/Quantile.

range(xs)

Specs

range([number]) :: Numerix.Common.maybe_float

The difference between the largest and smallest values in a list.

skewness(xs)

Specs

skewness([number]) :: Numerix.Common.maybe_float

The skewness of a frequency-distribution curve. It defines the extent to which a distribution differs from a normal distribution. Like kurtosis, it describes the shape of a probability distribution.

std_dev(xs)

Specs

std_dev([number]) :: Numerix.Common.maybe_float

The unbiased standard deviation from a sample. It measures the amount of variation of the vector.

variance(xs)

Specs

variance([number]) :: Numerix.Common.maybe_float

The unbiased population variance from a sample. It measures how far the vector is spread out from the mean.

weighted_covariance(xs, ys, weights)

Specs

weighted_covariance([number], [number], [number]) :: Numerix.Common.maybe_float

Calculates the weighted measure of how much two vectors change together.

weighted_mean(xs, weights)

Specs

weighted_mean([number], [number]) :: Numerix.Common.maybe_float

Calculates the weighted average of a list of numbers.