Numerix v0.6.0 Numerix.Statistics View Source

Common statistical functions.

Link to this section 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.

Link to this section 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.