Computes the geometric mean composition of a continuous mixture of point-counting data.
an object of class
The central composition assumes that the observed point-counting distribution is the combination of two sources of scatter: counting uncertainty and true geological dispersion.
[5 x n] matrix with
n being the number
of categories and the rows containing:
the ‘central’ composition.
the standard error for the central composition.
the overdispersion parameter, i.e. the coefficient of
variation of the underlying logistic normal
central computes a continuous
mixture model for each component (column)
separately. Covariance terms are not reported.
the lower limit of a ‘1 sigma’ region for
the upper limit of a ‘1 sigma’ region for
the mean square of the weighted deviates, a.k.a. reduced chi-square statistic.
the p-value for age homogeneity
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