# Questions tagged [bayesian]

Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.

5,463 questions
Filter by
Sorted by
Tagged with
660 views

### Do Bayesians ever argue there are cases in which their approach generalizes/overlaps with the frequentist approach?

Do Bayesians ever argue that their approach generalizes the frequentist approach, because one can use non-informative priors and therefore, can recover a typical frequentist model structure? Can ...
4k views

4k views

### What is the relationship between sample size and the influence of prior on posterior?

If we have a small sample size, will the prior distribution influence the posterior distribution a lot?
277 views

### Bayesian, MDL or ML interpretation of cross-validation?

Is there any known Bayesian, ML or MDL interpretation of cross-validation? Can I interpret cross validation as performing the right update on a specifically crafted prior?
3k views

### Calculate R-squared with JAGS and R

I have the following model that I am running in JAGS from R: ...
6k views

### Priors for log-normal models

I am trying to determine what the most appropriate non-informative priors are for the two parameters of a log-normal distribution (for an accelerated failure time model). I had been working with a ...
4k views

### Residual diagnostics in MCMC -based regression models

I've recently embarked on fitting regression mixed models in the Bayesian framework, using a MCMC algorithm (function MCMCglmm in R actually). I believe I have understood how to diagnose convergence ...
267 views

### How to move from some arbitrary “distance” to a probability distribution?

I'm doing some object recognition, and when I compare two images, I get some unbounded "distance" between the two images, representing how similar they are. This is somewhat useful, but it seems like ...
105 views

### How to calculate the probability that an algorithm classifies seven wines out of ten correctly when the true error is 0.23?

I am considering the following problem. Calculate the exact probability that an algorithm classifies seven wines out of ten correctly when the true error is 0.23. Should I solve this with Bayes' ...
555 views

### Frequentism and priors

Robby McKilliam says in a comment to this post: It should be pointed out that, from the frequentists point of view, there is no reason that you can't incorporate the prior knowledge into the model. ...
103 views

### Inference on random graph, with an application to mobile sensors

I've attended a course on Machine Learning and another one in Network Analysis, and I wonder if this two topics already intersect, in particular I'm interested in the following model: we have a ...