Implement gibbs sampling for the inference

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Implement Gibbs sampling for the inference of a single one-dimensional Gaussian, which we studied using maximum likelihood in section 22.1. Assign a broad Gaussian prior to µ and a broad gamma prior (24.2) to the precision parameter β = 1/σ². Each update of µ will involve a sample from a Gaussian distribution, and each update of σ requires a sample from a gamma distribution.

Reference no: EM131319117

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Implement gibbs sampling for the inference : Assign a broad Gaussian prior to µ and a broad gamma prior (24.2) to the precision parameter β = 1/σ2. Each update of µ will involve a sample from a Gaussian distribution, and each update of σ requires a sample from a gamma distribution.

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