For a sample x from a multivariate normal distribution with unknown mean and covariance matrix, test the null hypothesis that mean (x) == m.

For two dependent samples x and y from a multivariate normal distributions with unknown means and covariance matrices, test the null hypothesis that mean (x - y) == 0.

hotelling_t2test treats NaNs as missing values, and ignores the corresponding rows.

Name-Value pair arguments can be used to set statistical significance. "alpha" can be used to specify the significance level of the test (the default value is 0.05).

If h is 1 the null hypothesis is rejected, meaning that the tested sample does not come from a multivariate distribution with mean m, or in case of two dependent samples that they do not come from the same multivariate distribution. If h is 0, then the null hypothesis cannot be rejected and it can be assumed that it holds true.

The p-value of the test is returned in pval.

stats is a structure containing the value of the Hotelling’s $T^2$ test statistic in the field "Tsq", and the degrees of freedom of the F distribution in the fields "df1" and "df2". Under the null hypothesis, $(n-p)\; T^2\; /\; (p(n-1))$ has an F distribution with $p$ and $n-p$ degrees of freedom, where $n$ and $p$ are the numbers of samples and variables, respectively.

See also: hotelling_t2test2

Source Code: hotelling_t2test