# Tagged Questions

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

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### Confidence interval for Bayesian expected probability in categorical data

The context of the question is survey results analysis. I am focusing on categorical data : N respondents answer some questions and each question has $k_{q}$ choices. I want to compare what subgroups ...
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### PyMC sampling is slow

I'm using pymc2 to estimate the parameters of a normal distribution. My data has shape 50000 x 6. Basically, I have 50K independent distributions and I want to obtain the parameters for each of them, ...
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### How to correct for base rate when pooling different conditions?

My question is as follows: In each trial of my task there can either be a target or a distractor. For targets, the outcome can be true positive or false negative, whereas for the distractor the ...
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### Partitions, and Random variable indexes in Dirichlet Process

I am going over this tutorial and am confused by the notations on pages 14 and 15. Here is my understanding for the notations on page 14: $G\sim DP(\alpha,G_0)$: Means $G$ is a draw from a DP, with ...
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### How should I call the complement of a credible region?

Incredible interval/region? More explicitly, if I have a unimodal distribution with a 95% credible interval in [A,B], what would I call the complementary region ]A,B[? It is 100% credible region ...
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### Upper bounds on mixing times in MCMC for bayesian analysis in practice

I'm familiar with how, for a general markov chain with some transition kernel, the spectral gap and the log-Sobolev constant both provide an upper bound on mixing time. I also have heard people ...
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### Can a likelihood function be integrated to find the CDF and probabilities?

Likelihood analysis uses the likelihood function: $L(\Theta | data) = P(data | \Theta)$ to determine how likely it is that some value is the true population parameter ($\Theta$) compared to some ...