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BayesiaLabBayesiaLab User GuideInferenceApproximate Inference

Approximate Inference

Context

  • Approximate Inference is a backup method for performing inference if creating a Junction Tree for Exact Inference is prohibitive in terms of memory requirement or computation time.
  • Approximate Inference is based on the law of large numbers and uses network simulation to approximate the probabilities.
  • While Approximate Inference initially requires very little memory compared to Exact Inference, each inference step with Approximate Inference takes time to perform.

Usage

  • You can specify to use Approximate Inference by selecting Menu > Inference > Approximate Inference.

Bear in mind that most of BayesiaLab’s analysis tools and functions require Exact Inference. They will not work with Approximate Inference.

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