Parameter space refers to the set of all possible values that parameters in a statistical model can take. It is a fundamental concept in Bayesian statistics, as it defines the range of potential outcomes for the parameters being estimated and influences the decisions made based on the model. Understanding parameter space is crucial for assessing the implications of model assumptions and making optimal decisions based on the data available.
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