Return the estimated variance components

        Args:
            univariance:   Boolean indicator, if True variance components are normalized to sum up to 1 for each trait
        Returns:
            variance components of all random effects on all phenotypes [P, n_randEffs matrix]

def getVarianceComps(self, univariance=False):
        """
        Return the estimated variance components

        Args:
            univariance:   Boolean indicator, if True variance components are normalized to sum up to 1 for each trait
        Returns:
            variance components of all random effects on all phenotypes [P, n_randEffs matrix]
        """
        RV=sp.zeros((self.P,self.n_randEffs))
        for term_i in range(self.n_randEffs):
            RV[:,term_i] = self.getTraitCovar(term_i).diagonal()
        if univariance:
            RV /= RV.sum(1)[:,sp.newaxis]
        return RV