Covariance/variance.
procedure Covariance(const X: TVec; out aResult: double; NormN: boolean = true); overload;
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Parameters |
Description |
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X |
Defines sample (variable) values (observables). In this case X is treated as row and not (as normally) column vector. |
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aResult |
Returns the covariance (in this case equal to variance) for X vector elements. Because in this case X is represented as row vectro, the the result is simply scalar value E(X(T)*X)-E(X(T))E(X) = Var(X). |
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NormN |
If true (default value), the result will be normalized with number of observations (N), otherwise it will be normalized with N-1. |
The covariance between two real-valued random variables x and y,with expected values E(x)=mu and E(y)=nu is defined as:
where E(x), E(y) are x and y expected values.
For more info about covariance definition and properties check thd following links:
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