  The limited range in its abscissa of ranked letter frequency distributions
causes multiple functions to fit the observed distribution reasonably well. In
order to critically compare various functions, we apply the statistical model
selections on ten functions, using the texts of U.S. and Mexican presidential
speeches in the last 1-2 centuries. Dispite minor switching of ranking order of
certain letters during the temporal evolution for both datasets, the letter
usage is generally stable. The best fitting function, judged by either
least-square-error or by AIC/BIC model selection, is the Cocho/Beta function.
We also use a novel method to discover clusters of letters by their
observed-over-expected frequency ratios.
