# Tagged Questions

1answer
41 views

### MCMC and degree of freedoms (small number of observations)

I want to estimate a simple Regression. I have 20 observations and 10 Regression-parameters. The degrees of freedom are too small to get reliable point estimates and p-values. I found the following ...
0answers
25 views

### Thinning samples obtained using population MCMC methods

I am trying to use a Population Markov Chain Monte Carlo algorithm for parameter estimation in an ordinary differential equation model of gene regulation. The paper here gives a good summary of ...
1answer
39 views

### Bayesian model averaging for variable selection in R

I am trying to use Bayesian model averaging for variable selection with a large number of variables. In R, the BMS package allows to apply the method, with the option of using MCMC sampler (Metropolis ...
1answer
34 views

### How to find the support of the posterior distribution to apply Metropolis-Hastings MCMC algorithm?

I am trying to sample from a posterior distribution using a MCMC algorithm using the Metropolis-Hastings sampler. How should I deal with the situations where I'm stuck in regions of the posterior ...
0answers
54 views

### Can I do a Bayesian search with no prior?

If I do a Bayesian mcmc search with a flat prior such as uniform distribution with very large lower and upper limits, then multiplying the likelihood by the prior equates to simply multiplying the ...
3answers
74 views

### MCMC for an explicitly uncomputable prior?

I am trying to sample from a posterior distribution and I only have an explicit formula for likelihood but I can sample from the prior distribution. How can I sample from the posterior distribution ...
2answers
91 views

### How to sample using MCMC from a posterior distribution in general?

Assume one has the posterior distribution of a parameter, $p(\theta|y)$ and what I mean by having it is that for each point of $\theta$, one can use Monte Carlo method+MCMC to calculate the ...
0answers
57 views

### Model validation in Bayesian statistics from a model with latent variables

I am working with some two-regime autoregressive models first introduced by Hamilton in 1989. The specific models is of no great concern to my question, but some variables within my autoregressive ...
0answers
31 views

### Simulating from Posterior Predictive Over Many Periods

Suppose I obtain a posterior distribution through MCMC. This will give some simulated values for the parameters to a statistical model. If I calculate the posterior predictive distribution one period ...
2answers
143 views

### Good non-informative priors for estimating the parameters of a Gaussian with MCMC (using PyMC)?

Say I want to estimate the mean $\mu \in [0, 10]$ of some Gaussian data $\mathbf{x}$ with known variance $\sigma^2 = 1$ using MCMC. Usually I'd use a prior like $\mu \sim \mathrm{Uniform}(0, 10)$ and ...
1answer
68 views

### Hamiltonian Monte Carlo and discrete parameter spaces

I've just started building models in stan; to build familiarity with the tool, I'm working through some of the exercises in Bayesian Data Analysis (2nd ed.). The Waterbuck exercise supposes that the ...
1answer
40 views

### Estimating Bayes factor in moderately high dimension (about 100)

There is a large literature about the estimation of bayes factor using e.g. importance sampling (e.g. https://www.rocq.inria.fr/axis/COMPSTAT2010/TU-marin_paper.pdf). Most (all?) of them investigate ...
0answers
29 views

### How to calculate gelman and rubin convergence diagnostics in Excel

Does anyone know how to calculate the gelman and rubin convergence diagnostics in Excel. I'm trying to understand the steps in the formula, but not sure that I doing it correctly. I know it can be ...
1answer
216 views

### Hierarchical Bayesian analysis on difference of proportions

Why Hierarchical? : I've tried researching this problem, and from what I understand, this is a "hierarchical" problem, because you are making observations about observations from a population, rather ...
2answers
117 views

### Implementing MCMC

I'm writing an MCMC algorithm in R and I'm wondering about the following: say we have two parameters, $\theta_1$ and $\theta_2$. I want to update each one at a time from the corresponding posterior ...
0answers
44 views

### Transform log posterior probabilities for Bayesian model averaging

I have four models, each one is run with MCMC on a large number phylogenetic trees. Each resulting model has an associated log posterior probability (sum of the log likelihood and log prior). Since I ...
1answer
47 views

1answer
1k views

### WinBUGS error with zero values in binomial distribution: value of order of binomial <expr> must be greater than zero

It seems that WinBUGS has problems if it has only zero draws from one binomial distribution: 1. case - simple model ...
1answer
159 views

### Computing 2 independent models at once leads to wrong results in WinBUGS

I wanted to compare how two different (independent) models perform under winbugs, So I created code like: ...