# 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.

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### The 'R2jags::autojags()' Function Doesn't Converge

I'm running the following code in R: ...
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### Statistical Fact: Heads to win, 1000 people flip coins, after 10 flips there is a winner every time [closed]

I was listening to a podcast by NDGT (Neil deGrasse Tyson, a prominent scientist) and he posed a simple thought experiment to illustrate the susceptibilities to cognitive bias. I am guilty of such ...
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1 vote
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### Calculating Probability Using Bayes? [closed]

A recent survey of residents in Texas concluded that 55% of Austin city residents and 46% of Houston city residents broke a bone at some point during their childhood. Let’s say Austin has 5200 ...
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1 vote
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### Bayesian approach to removing outliers from a normal distribution

A lot of what I've seen for Bayesian approaches to removing outliers is for a linear model, not a normal distribution. Is there a way we can take a Bayesian approach to remove outliers from a normal ...
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### Trying to replicate figures from Bayesian statistics without tears: A sampling-resampling perspective, but failed [migrated]

I'm trying to replicate the three figures from the paper Bayesian statistics without tears: A sampling-resampling perspective, which can be found here: http://hedibert.org/wp-content/uploads/2013/12/...
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### Bayes Factor for two groups comparison with unequal variances from bayes.t.test in bolstad R package [closed]

After asking for a bayesian version of Welch test in a stackoverflow previous thread: https://stackoverflow.com/questions/72171331/bayes-factor-for-two-groups-comparison-with-unequal-variances-is-...
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### How can I calculate Posterior Distribution, analytically with given information?

The image below shows that the posterior distribution is as follows with given information: I wonder how the posterior has been calculated, analytically.
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### How to forecast sales for entire current month taking into account sales from half of month?

Good afternoon! I want to forecast sales for current month. Since I already know sales for two weeks of current month, I want to incorporate this information into forecast for the whole current month, ...
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1 vote
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### Bayesian statistics: what is the variable we are integrating in?

This is a screenshot from Bayesian Data Analysis by Gelman. I am a little bit confused by Equation 1.4 (first and second lines), having read Equation 1.3. In Equation 1.3, the variable of integration ...
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1 vote
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### What is Gaussian approximation for the variance of a function?

In Orre 2000, the author provides an asymptotic approach to computing the variance of information component and conditioned posterior distribution. In part 2.2 weights and information components So ...
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### Methods for modelling distributions?

As predictor X I have particle size distributions and I would like to run a model y ~ X. I.e. each trial has a response ...
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### Conditional probability problem (Bayes Theorem ?) [closed]

Hello, basically, I can't find 1/2 for the very last question. I tried to use the Baye's Theorem, but it wasn't successful Could someone help me ?
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### SAS Bayesian 95% credible intervals for proportions or crosstabs [closed]

I am trying to find SAS code for figuring 95% credible intervals as relates to differences two proportions or a contingency table. I see there is proc MCMC but the examples I see are 1 proportion, and ...
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### Confidence interval for the parameter of a random variable

I am studying statistics, and I came across a problem that I am not sure if what I am doing is correct or if there is some other way to do this. Any feedback is appreciated. I divided in 2 problems, ...
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### Modification of Outliers

I have a practical / applied statistics question. I'm dealing with a specialized dataset with a very small sample (i.e. n < 10). In the sequence of observations, it is possible that a new ...
1 vote
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### Are these Bayesian Inference?

I am trying to understand what is and what is not considered Bayesian inference. Let say I am to estimate a parameter or a vector of parameters say $\theta$ and I have data on some features of the ...
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### Bayesian Additive Regression Trees: Zero-inflated explanatory variable, will it influence the model and variable selection?

I am currently implementing BART to model the distribution of a marine species (using the embarcadero package). I am using environmental covariates, but also some prey data that are very-much zero-...
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### Variational Inference Mean-Field Gaussian

I am new to variational inference and got very confused about some basic ideas. We want to use the mean-field gaussian family to approximate a complicated high-dimensional distribution. I want to ...
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