function MBoxTest(const X1: TMtx; const X2: TMtx; out Signif: Double; out hRes: THypothesisResult; out df1: Integer; out df2: Integer; const Alpha: Double): Double;
M-Box test for equal covariances.
| # | Name | Description |
|---|---|---|
| 1 | X1 | First matrix. The number of columns for X1 and X2 must be equal, otherwise an exception is raised. |
| 2 | X2 | Second matrix. The number of columns for X1 and X2 must be equal, otherwise an exception is raised. |
| 3 | df1 | Nominator degrees of freedom. |
| 4 | df2 | Denominator degrees of freedom. |
| 5 | Alpha | Defines the desired significance level. |
| 6 | hRes | Returns the result of the null hypothesis. |
| 7 | Signif | (Significance level) returns the probability of observing the given result |
Returns: Double
Remarks:
Performs M-Box test for equal covariances. In this case the null hypothesis is that X1 and X2 covariances are equal and the alternative hypothesis is that X1 and X2 covariances are not equal.
Examples
Uses MtxExpr, Statistics, Math387;
procedure Example;
var X1,X2: Matrix;
MB,sign: double;
hres: THypothesisResult;
df1, df2: integer;
begin
X1.SetIt(5,3,false,[23,45,15, 40,85,18, 215,307,60, 110,110,50, 65,105,24]);
X2.SetIt(5,3,false,[277,230,63, 153,80,29, 306,440,105, 252,350,175, 143,205,42]);
MB := MBoxTest(X1,X2,sign,hres, df1, df2, 0.05);
// MB : 27,16221062
// Sign : 0,01619810
// Sign < Alpha meaning hres = hrReject i.e. covariance matrices are significantly different.
end;See Also: Statistics.HotellingT2One