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better wording around norm_type

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conrad
2022-06-21 23:13:11 +10:00
parent 46ca336070
commit 6f5e2e72bf
1 changed files with 24 additions and 5 deletions
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@@ -14893,9 +14893,21 @@ For vectors, <i>X</i> and <i>Y</i> must have the same number of elements
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The default <i>norm_type&thinsp;=&thinsp;0</i> performs normalisation using <i>N-1</i> (where <i>N</i> is the number of observations),
providing the best unbiased estimation of the covariance matrix (if the observations are from a normal distribution).
Using <i>norm_type&thinsp;=&thinsp;1</i> causes normalisation to be done using <i>N</i>, which provides the second moment matrix of the observations about their mean
The <i>norm_type</i> argument is optional; by default <i>norm_type&thinsp;=&thinsp;0</i> is used
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the <i>norm_type</i> argument controls the type of normalisation used, with <i>N</i> denoting the number of observations:
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for <i>norm_type&thinsp;=&thinsp;0</i>, normalisation is done using <i>N-1</i>,
providing the best unbiased estimation of the covariance matrix (if the observations are from a normal distribution)
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for <i>norm_type&thinsp;=&thinsp;1</i>, normalisation is done using <i>N</i>,
which provides the second moment matrix of the observations about their mean
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</ul>
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@@ -14954,8 +14966,15 @@ For vectors, <i>X</i> and <i>Y</i> must have the same number of elements
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The default <i>norm_type&thinsp;=&thinsp;0</i> performs normalisation of the correlation matrix using <i>N-1</i> (where <i>N</i> is the number of observations).
Using <i>norm_type&thinsp;=&thinsp;1</i> causes normalisation to be done using <i>N</i>
The <i>norm_type</i> argument is optional; by default <i>norm_type&thinsp;=&thinsp;0</i> is used
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the <i>norm_type</i> argument controls the type of normalisation used, with <i>N</i> denoting the number of observations:
<ul>
<li>for <i>norm_type&thinsp;=&thinsp;0</i>, normalisation is done using <i>N-1</i></li>
<li>for <i>norm_type&thinsp;=&thinsp;1</i>, normalisation is done using <i>N</i></li>
</ul>
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