(mean values)
Calculates the mean of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
Calculates the mean of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
(normalise-probabilities v)
Normalises a numerical probability vector, i.e. to a vector where all elements sum to 1.0. A zero vector will be set set to [1/n .... 1/n].
Normalises a numerical probability vector, i.e. to a vector where all elements sum to 1.0. A zero vector will be set set to [1/n .... 1/n].
(sd values)
Calculates the sample standard deviation of a set of values. Values may be scalars, vectors or higher-dimensional matrices.
Calculates the sample standard deviation of a set of values. Values may be scalars, vectors or higher-dimensional matrices.
(sum values)
Calculates the sum of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
Calculates the sum of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
(sum-of-squares values)
Calculates the sum of squares of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
Calculates the sum of squares of a collection of values. Values may be scalars, vectors or higher-dimensional matrices.
(variance values)
Calculates the unbiased sample variance of a set of values. Values may be scalars, vectors or higher-dimensional matrices.
Calculates the unbiased sample variance of a set of values. Values may be scalars, vectors or higher-dimensional matrices.
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