central.counts {provenance}

Calculate central compositions

Description

Computes the logratio mean composition of a continuous mixture of point-counting data.

Usage

## S3 method for class 'counts'
central(x, ...)

Arguments

x

an object of class counts

...

optional arguments

Details

The central composition assumes that the observed point-counting distribution is the combination of two sources of scatter: counting uncertainty and true geological dispersion.

Value

an [5 x n] matrix with n being the number of categories and the rows containing:

theta

the ‘central’ composition.

err

the standard error for the central composition.

sigma

the overdispersion parameter, i.e. the coefficient of variation of the underlying logistic normal distribution. central computes a continuous mixture model for each component (column) separately. Covariance terms are not reported.

LL

the lower limit of a ‘1 sigma’ region for theta.

UL

the upper limit of a ‘1 sigma’ region for theta.

mswd

the mean square of the weighted deviates, a.k.a. reduced chi-square statistic.

p.value

the p-value for age homogeneity