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
covariance(x, y)
View Sourcecovariance(Numerix.Common.vector(), Numerix.Common.vector()) :: 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(x)
View Sourcekurtosis(Numerix.Common.vector()) :: 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(x)
View Sourcemean(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The average of a list of numbers.
median(x)
View Sourcemedian(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The middle value in a list of numbers.
mode(x)
View Sourcemode(Numerix.Common.vector()) :: Numerix.Common.maybe_vector()
The most frequent value(s) in a list.
moment(x, n)
View Sourcemoment(Numerix.Common.vector(), pos_integer()) :: Numerix.Common.maybe_float()
The nth moment about the mean for a sample. Used to calculate skewness and kurtosis.
percentile(x, p)
View Sourcepercentile(Numerix.Common.vector(), 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(x, y)
View Sourcepopulation_covariance(Numerix.Common.vector(), Numerix.Common.vector()) :: 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(x)
View Sourcepopulation_std_dev(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The standard deviation for a full population. It measures the amount of variation of the vector.
population_variance(x)
View Sourcepopulation_variance(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The variance for a full population. It measures how far the vector is spread out from the mean.
quantile(x, tau)
View Sourcequantile(Numerix.Common.vector(), 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(x)
View Sourcerange(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The difference between the largest and smallest values in a list.
skewness(x)
View Sourceskewness(Numerix.Common.vector()) :: 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(x)
View Sourcestd_dev(Numerix.Common.vector()) :: Numerix.Common.maybe_float()
The unbiased standard deviation from a sample. It measures the amount of variation of the vector.
variance(x)
View Sourcevariance(Numerix.Common.vector()) :: 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(x, y, w)
View Sourceweighted_covariance( Numerix.Common.vector(), Numerix.Common.vector(), Numerix.Common.vector() ) :: Numerix.Common.maybe_float()
Calculates the weighted measure of how much two vectors change together.
weighted_mean(x, w)
View Sourceweighted_mean(Numerix.Common.vector(), Numerix.Common.vector()) :: Numerix.Common.maybe_float()
Calculates the weighted average of a list of numbers.