Search Results
Search type | Search syntax |
---|---|
Tags | [tag] |
Exact | "words here" |
Author |
user:1234 user:me (yours) |
Score |
score:3 (3+) score:0 (none) |
Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
Views | views:250 |
Code | code:"if (foo != bar)" |
Sections |
title:apples body:"apples oranges" |
URL | url:"*.example.com" |
Saves | in:saves |
Status |
closed:yes duplicate:no migrated:no wiki:no |
Types |
is:question is:answer |
Exclude |
-[tag] -apples |
For more details on advanced search visit our help page |
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.
3
votes
0
answers
91
views
Using non-parametric bootstrap to assess relative difference between means of two samples
To me, the procedure looks like we are interpreting non-parametric bootstrap as Bayesian model that has nothing to do with classical frequentist statistical significance since in that case we should bootstrap …
0
votes
2
answers
173
views
Bayesian approach for getting the distribution of sum of predicted values
I'm interested in the Bayesian approach (I already found the same problem solved by frequentists) and I would appreciate an intuitive explanation and, if possible, solve it with as little math as possible …
0
votes
0
answers
44
views
Bayesian A/B testing with normal conjugate model for huge (non-normal) sample sizes
I'm thinking about switching from the frequentist to Bayesian approach (easier interpretation). …