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A simulation-based approach is proposed for approximating a Bayesian analysis. Parameters and data are simulated from a Bayesian model and inference about a parameter is performed by exploring the set of simulated parameter values conditional on a set of values of a simulated statistic. The approach is used to learn about parameters of a streaky model on the basis of a statistic used to measure streakiness. The method is illustrated to detect streakiness in baseball hitting data and basketball shooting data.
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Albert et al. (2001) studied this question.
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