Before the advent of Optimality Theory (OT), quantitative
variation patterns were usually regarded as the outcome of a
selection between categorical grammars (see Bailey, 1973;
Bickerton, 1973, among others). In a constraint-based approach,
like OT, one is able to account for variation without resorting
to a separate grammar for each variant, since the framework
allows for variation to be encoded in (and therefore predicted
by) a single grammar, through variable ranking (or crucial
nonranking) of constraints. Along the lines of Reynolds (1994)
and Anttila (1997), this study supports the view that, from
the predictions determined by a language-specific set of variably
ranked constraints, it is possible to establish quantitatively
the probability of application of each variant inherent to the
variation process. As a consequence, the analysis of across-word
regressive assimilation in Picard attempts to incorporate into
the grammar of the language both abstract knowledge and
quantitative patterns of language use.