Mahalanobis distance example by hand
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Rango tamilyogiThe Mahalanobis distance is a measure of the distance between a point P and a distribution D, as explained here. I will not go into details as there are many related articles that explain more about it. I will only implement it and show how it detects outliers. The complete source code in R can be found...Mahalanobis’ distance identifies observations that lie far away from the centre of the data cloud, giving less weight to variables with large variances or to groups of highly correlated variables (Joliffe 1986). This distance is often preferred to the Euclidean distance which ignores the covariance structure and treats all variables equally. 45 cal hornady great plains bullets
It is calculated as: D 2 = ( x − m) T C − 1 ( x − m) where: D 2 = Mahalanobis distance x = Vector of data m = Vector of mean values of independent variables C − 1 = Inverse Covariance matrix of independent variables T = Indicates vector should be transposed. This page provides a detailed explanation (with examples from landscape analysis).

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Mahalanobis distance example by hand

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Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand

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If you are using a module and expect the file to exist on the remote see the remote_src option

Mahalanobis distance example by hand

Mahalanobis distance example by hand

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Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand



Mahalanobis distance example by hand

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Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand

Mahalanobis distance example by hand