1 - Bayesian Statistic
Frequentist
Bayesian Modeling
Posts about Bayesian modeling. The contents are based on STAT598 ABM lecture.
2 - Binomial Example Continued
In the last post, we talked about the binomial example from Bayesian perspective. We only considered using the uniform prior distribution for \(\theta\). It ...
3 - Mean-Only Normal
Normal Distribution Normal distribution is major statistical model. Thanks to central limit theorem, many statistical models justify using the normal model. ...
4 - Two Parameters Normal
Multiparameter Model
5 - Hierarchical Model I
Many statistical applications have multiple parameters related to each other. In some cases, similar parameters apply to different subsets of data with a com...
6 - Hierarchical Model 2
In this post, we will discuss about hierarchical model based on normal distributions where several groups are observed with different means. Let’s look at an...
7 - Monte Carlo Approximation
So far we have computed the posterior distribution by simulating directly from a combinations of standard distributions such as normal, beta, Poisson, and so...
8 - Markov Chain Monte Carlo
Markov Chain Monte Carlo(MCMC) is a general method of drawing samples from a target distribution with relatively faster speed to converge and its capability ...
9 - Metropolis Hastings Proof
This post is not done…
10 - Convergence Diagnostic
We have talked about Markov Chain Monte Carlo methods such as Metropolis-Hastings or Gibbs Sampler. And the key to successfully draw samples from these sampl...
11 - Model Checking
We have discussed how to construct models and how to simulate its distribution. However, if we do not check adequacy of the fit of the model, the model can b...
Metropolis Hastings Example
암호 해독 문제와 변환 함수