function HotellingT2One(const X: TMtx; const Means: TVec; out Signif: Double; out hRes: THypothesisResult; const Alpha: Double): Double;
One-sample Hotelling T2 test.
| # | Name | Description |
|---|---|---|
| 1 | X | Stores test values, each row representing different case and each column representing different response variable. The assumption is data is approximately multivariate normal. |
| 2 | Means | Stores estimated mean for each variable. An exception is raised if Means Length is not equal to Data columns. If Means is nil, the assumption is means are equal. |
| 3 | Signif | (Significance level) returns the probability of observing the given result by chance given that the null hypothesis is true. |
| 4 | hRes | Returns the result of the null hypothesis (default assumption is variable means are equal to Means vector). |
| 5 | Alpha | Defines the desired significance level. If the significance probability (Signif) is bellow the desired significance (Alpha), the null hypothesis is rejected. |
Returns: Double - Hotelling T2 Statistics for one-sample test.
Remarks:
Performs one-sample Hotelling T2 test. The one-sample T2 is used to test hypotheses about a set of means simultaneously. The null hypothesis is that sample means are equal to Means vector values. The following assumptions are made when using T2:
- The population follows the multivariate normal distribution.
- The members of the sample are independent.
The one-sample T2 test may also be applied to the situation in which two samples are to be compared that had a natural pairing between two observation vectors. In this case the differences between the first and second measurements are formed and then used as data in unpaired Hotelling T2 test.