Linked Questions

3
votes
2answers
593 views

What is the intuition behind the Metropolis-Hastings Algorithm? [duplicate]

I've been studying Bayesian Statistics lately, and just came across the Metropolis-Hastings Algorithm. I understand that the goal is to sample from an intractable posterior - but I'm not really able ...
2
votes
0answers
185 views

What is Bayesian and Monte Carlo Simulation? [duplicate]

Can someone explain in plain language for a layperson what are Bayesian and Monte Carlo simulations and the relationship between the two? I thought Bayesian was the same as Monte Carlo Simulation...
1
vote
0answers
21 views

OpenBUGS intuition with data [duplicate]

I've recently discovered Bayesian statistics, currently I am experimenting with Openbugs, yet I cant grasp the concept of what happens with the inputted data. I understand mcmc, yet all of examples I'...
1
vote
0answers
21 views

Metropolis Hastings algorithm and Markov chains [duplicate]

Why does Metropolis Hastings algorithm need/make a sequence of interdependent samples, i.e., a Markov chain in order to generate a posterior distribution?
19
votes
4answers
4k views

Posterior distribution and MCMC [duplicate]

I have read something like 6 articles on Markov Chain Monte carlo methods, there are a couple of basic points I can't seem to wrap my head around. How can you "draw samples from the posterior ...
13
votes
2answers
19k views

Bayesian logit model - intuitive explanation?

I must confess that I previously haven't heard of that term in any of my classes, undergrad or grad. What does it mean for a logistic regression to be Bayesian? I'm looking for an explanation with a ...
14
votes
4answers
5k views

A practical example for MCMC

I was going through some lectures related to MCMC. However, I don't find a good example of how it is used. Can anyone give me a concrete example. All I can see that is they run a Markov chain and say ...
9
votes
1answer
5k views

MCMC/EM limitations? MCMC over EM?

I am currently learning hierarchical Bayesian models using JAGS from R, and also pymc using Python ("Bayesian Methods for Hackers"). I can get some intuition from this post: "you will end up with a ...
8
votes
2answers
2k views

What are Monte Carlo simulations?

Is Monte Carlo Simulation the same as just conducting experiment several times and then averaging results? Why is it then called like that?
12
votes
1answer
507 views

MCMC; Can we be sure that we have a ''pure'' and ''large enough'' sample from the posterior? How can it work if we are not?

Referring to this thread: How would you explain Markov Chain Monte Carlo (MCMC) to a layperson?. I can see that it is a combination of Markov Chains and Monte Carlo: a Markov chain is created with ...
5
votes
2answers
209 views

Using Markov Chain Monte Carlo to compute the chances that a particular solitaire laid out with 52 cards would come out successfully

Based on some references I got from another question I learned that: While convalescing from an illness in 1946, Stan Ulam was playing solitaire. It, then, occurred to him to try to compute the ...
3
votes
1answer
662 views

Sampling with Metropolis-Hastings

In Metropolis-Hastings sampling, if every draw of my proposal distribution (Q) is independent from the previous draw, is the convergence to the stationary distribution still guaranteed? To be more ...
1
vote
1answer
352 views

how to get the stationary distribution of MCMC (Markov Chain Monte Carlo) model

Based on my reading some course notes as well as the answers and comments to this SO post I started thinking about the general steps for creating a stationary distribution. Assuming my problem were ...