  We show that the exponent in the inverse power law of word frequencies for
the monkey-at-the-typewriter model of Zipf's law will tend towards -1 under
broad conditions as the alphabet size increases to infinity and the letter
probabilities are specified as the values from a random division of the unit
interval. This is proved utilizing a strong limit theorem for log-spacings due
to Shao and Hahn.

Probability