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Author: stdlib-bot

stats/base/ndarray/covarmtk/coverage.ndjson

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stats/base/ndarray/covarmtk/index.html

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 *
 * -   The function expects the following ndarrays in order:
 *
-*     -   first one-dimensional input ndarray.
-*     -   second one-dimensional input ndarray.
-*     -   a zero-dimensional ndarray specifying degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the covariance according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the population covariance, setting this parameter to `0` is the standard choice (i.e., the provided arrays contain data constituting entire populations). When computing the unbiased sample covariance, setting this parameter to `1` is the standard choice (i.e., the provided arrays contain data sampled from larger populations; this is commonly referred to as Bessel's correction).
-*     -   a zero-dimensional ndarray specifying mean of the first one-dimensional ndarray.
-*     -   a zero-dimensional ndarray specifying mean of the second one-dimensional ndarray.
+*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the covariance according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of elements in each input ndarray. When computing the population covariance, setting this parameter to `0` is the standard choice (i.e., the provided arrays contain data constituting entire populations). When computing the unbiased sample covariance, setting this parameter to `1` is the standard choice (i.e., the provided arrays contain data sampled from larger populations; this is commonly referred to as Bessel's correction).
+*     -   a zero-dimensional ndarray specifying the mean of the first one-dimensional ndarray.
+*     -   a zero-dimensional ndarray specifying the mean of the second one-dimensional ndarray.
 *
 * @param {ArrayLikeObject&lt;Object&gt;} arrays - array-like object containing input ndarrays
 * @returns {number} covariance
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             <div class='footer quiet pad2 space-top1 center small'>
                 Code coverage generated by
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