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Updated: Feb 7, 2026

A Rapid Method for Modeling a Variable Cycle Engine
Published on: August 13, 2019
Modeling bout-pause response patterns in variable-ratio and variable-interval schedules using hierarchical Bayesian
Hiroshi Matsui1, Kota Yamada2, Takayuki Sakagami2
1Department of Psychology, Keio University, Tokyo, Japan; Japan Society for the Promotion of Science, Tokyo, Japan.
Abstract:
Streams of operant responses are arranged in bouts separated by pauses and differences in performance in reinforcement schedules with identical inter-reinforcement intervals (IRIs) are primarily due to differences in within-bout response rate, not in bout-initiation rate. The present study used hierarchical Bayesian modeling as a new method to quantify the properties of the response bout. A Bernoulli distribution was utilized to express the probability to stay in bout/pause, while a Poisson distribution was utilized to quantify the within-bout response rates. We compared bout/pause patterns between variable-ratio (VR) and variable-interval (VI) schedules across IRIs. The model estimation revealed no difference in within-bout staying probability between schedules. However, response rates of within-bout responses were higher in VR than VI across IRIs. These results are consistent with previous analyses using a log-survivor plot to describe within-bout responses and bouts-initiation responses. In addition, a simulation study was performed to examine how sensitively the model estimate the parameters according to different bout initiation rates. These result showed that the within-bout staying probability was affected by changes in between-bout while within-bout response rate parameters were not. This suggests model estimation robustness of the model estimation to dissociate within-bout and between-bout parameters during different reinforcement schedules.
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