Numerix v0.4.2 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
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 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.
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.
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.
weighted_covariance([number], [number], [number]) :: Numerix.Common.maybe_float
Calculates the weighted measure of how much two vectors change together.
Calculates the weighted average of a list of numbers.