ECE 595ML Lecture 12.2: Bayesian Parameter Estimation - Choosing Priors

By Stanley H. Chan

Electrical and Computer Engineering, Purdue University, West Lafayette, IN

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Researchers should cite this work as follows:

  • Stanley H. Chan (2020), "ECE 595ML Lecture 12.2: Bayesian Parameter Estimation - Choosing Priors," https://nanohub.org/resources/32447.

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WTHR 200, Purdue University, West Lafayette, IN

Tags

  1. Bayesian
  2. Bayesian statistics
ECE 595ML Lecture 12.2: Bayesian Parameter Estimation - Choosing Priors
  • Lecture 12.2: BayesianParameterEstimation- 1. Lecture 12.2: BayesianParamete… 0
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  • Outline 2. Outline 10.21021021021021
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  • Prior for µ 3. Prior for µ 66.066066066066071
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  • Prior for σ2 4. Prior for σ2 197.43076409743077
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  • Prior for σ2 5. Prior for σ2 334.16750083416753
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  • Prior for σ2 6. Prior for σ2 459.95995995996
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  • Prior for Both µ and σ2 7. Prior for Both µ and σ2 484.01735068401734
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  • Priors for High-dimension Gaussians 8. Priors for High-dimension Gaus… 575.709042375709
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  • Conjugate Prior 9. Conjugate Prior 642.37570904237577
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  • Reading List 10. Reading List 801.50150150150148
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  • Appendix 11. Appendix 847.51418084751424
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  • Prior for σ2: Solution 12. Prior for σ2: Solution 852.81948615281954
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  • Prior for σ2: Solution 13. Prior for σ2: Solution 853.52018685352027
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  • Prior for Both µ and σ2: Detailed Derivation 14. Prior for Both µ and σ2: Det… 854.2876209542876
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  • Prior for Both µ and σ2: Detailed Derivation 15. Prior for Both µ and σ2: Det… 854.98832165498834
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  • Prior for Both µ and σ2: Detailed Derivation 16. Prior for Both µ and σ2: Det… 855.72238905572237
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