Chapter 06.
Posterior Approximation with the Gibbs sampler
๋ณธ ํฌ์คํ ์ First Course in Bayesian Statistical Methods๋ฅผ ์ฐธ๊ณ ํ์๋ค.
1. A Semi-conjugate prior distribution
2. Discrete approximations
3. Sampling from the conditional distributions
4. Gibbs Sampling
5. General properties of the Gibbs sampler
6. Introduction to MCMC diagnostics
Conclusion
semi-conjugate ๋ถํฌ๋ฅผ ๋ชจ๋ ์๋ฉด full conditional probability๋ฅผ ์๋ ๊ฒ๊ณผ ๊ฑฐ์ ๊ฐ๋ค.
ํน์ ๊ถ๊ธํ ์ ์ด๋ ์๋ชป๋ ๋ด์ฉ์ด ์๋ค๋ฉด, ๋๊ธ๋ก ์๋ ค์ฃผ์๋ฉด ์ ๊ทน ๋ฐ์ํ๋๋ก ํ๊ฒ ์ต๋๋ค.