Abstract
This paper investigates the variables that could affect the stutter ratio (SR). Bayesian modelling techniques are used to model the distribution of the SR using the parameters identified: the locus and the longest uninterrupted sequence (LUS). The final model gives an expected estimate for the SR as well as the distribution about this estimate.
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