  The date of the first performance of a play of Shakespeare's time must
usually be guessed with reference to multiple indirect external sources, or to
some aspect of the content or style of the play. Identifying these dates is
important to literary history and to accounts of developing authorial styles,
such as Shakespeare's. In this study, we took a set of Shakespeare-era plays
(181 plays from the period 1585--1610), added the best-guess dates for them
from a standard reference work as metadata, and calculated a set of
probabilities of individual words in these samples. We applied 11 regression
methods to predict the dates of the plays at an 80/20 training/test split. We
withdrew one play at a time, used the best-guess date metadata with the
probabilities and weightings to infer its date, and thus built a model of
date-probabilities interaction. We introduced a memetic algorithm-based
Continued Fraction Regression (CFR) which delivered models using a small number
of variables, leading to an interpretable model and reduced dimensionality. An
in-depth analysis of the most commonly occurring 20 words in the CFR models in
100 independent runs helps explain the trends in linguistic and stylistic
terms. The analysis with the subset of words revealed an interesting
correlation of signature words with the Shakespeare-era play's genre.
