# Tagged Questions

Bayesian inference is a method of statistical inference which uses Bayes' theorem to find probability estimates of parameters or hypotheses.

38 views

### Bayesian approach on games of chance with physical devices

Suppose we alter side 6 of a die to appear more than 1/6th of the time. We do not know the actual proportion of the time each side of the die will appear because all or some of the other 5 sides do ...
267 views

### Is it possible to interpret the bootstrap from a Bayesian perspective?

Ok, this is a question that keeps me up at night. Can the bootstrap procedure be interpreted as approximating some Bayesian procedure (except for the Bayesian bootstrap)? I really like the Bayesian ...
74 views

### Using JAGS for bayesian parameter estimation

I am using JAGS in R to construct a probabilistic graph model and estimate the corresponding parameters. The models is described as follows: ...
82 views

### How can I combine data from 2 separate experiments?

I am a scientist and by no means a statistician. I have, I think, a very basic question for you all. I have performed the same experiment twice (analyzing levels of a certain protein) and am ...
133 views

### Specify a Zero-inflated (Hurdle) Gamma Model in JAGS/BUGS

I'm trying to use a zero-inflated gamma model (or a gamma 'hurdle' model). The model is a mixture of logistic regression and generalized linear modeling. I can do this analysis in two steps: 1) do a ...
125 views

### Estimating parameters in multivariate classification resulting zero determinant sample covariance matrix

Newbie here typesetting my question, so excuse me if this don't work. I am trying to give a bayesian classifier for a multivariate classification problem where input is assumed to have multivariate ...
75 views

### Are posterior probabilities from a Naive Bayes classifier reliable?

I have read that the posterior probabilities of Naive Bayes classifiers are unreliable. Is this true? and if so, in what sense, and why? Specifically, I am interested to know if the probabilities can ...
39 views

### Bayesian analysis problem

The problem in hand is that the prior distribution which I have received from experts (loan recovery data) ranges from 0 to 100%. Thus a beta distribution was assumed. Where as the actual data shows ...
35 views

### Prediction and credible interval

I am wondering if prediction interval and credible interval evaluate the same thing. For instance with a linear regression, when you estimate the prediction interval of a fitted values, you estimate ...
79 views

### Improper Bayesian Prior

I was reading TPE by Lehmann andCasella where I came through this example: If $X\sim\text{Bin}(n,p)$ and we consider a $\text{beta}(a,b)$ prior for $p$. The Bayes estimator in this case is ...
168 views

### Why does Bayes' Theorem work graphically?

From a mathematical standpoint Bayes' Theorem makes perfect sense to me (i.e., deriving and proving), but what I do not know is whether or not there is a nice geometric or graphical argument that can ...
119 views

### How does the beta prior affect the posterior under a binomial likelihood

I have two questions, Question 1: How can I show that the posterior distribution is a beta distribution if the likelihood is binomial and the prior is a beta Question 2: How does choices the prior ...
27 views

### Classification with Bayes Network (deal)

I am working with multiple binary vectors e.g., A,B,C,D,E,F,G,H. I want to find the classification between them. I have tried the following: ...
105 views

### Why Bayesian logistic (probit) regression instead of standard logistic (probit) regression?

I wonder under what condition I should use Bayesian logistic regression instead of standard logistic regression, or vice verse? I have individual-level data regarding whether a person purchase a ...
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 ...
42 views

### References for Bayesian group-Lasso for probit/logit regression

Does anyone have a paper or other references on Bayesian group-Lasso for probit/logit model or GLM (generalized linear models) in general? I could not find any paper that explicitly deals with this.
70 views

### Running regularized logistic regressions on very large datasets

I want to run a regularized logistic regression on a dataset with 25 million observations and about a 1000 mostly non-sparse columns with non-ignorable weights. My first choice would be BayesGLM, ...
30 views

### Bayesian model averaging in the case of large number of predictors

In the context of a linear factor model, Bayesian Model Averaging (BMA) is used to obtain the posterior probability of all possible combinations of predictors. A final model is obtained as a weighted ...
83 views

### What kind of plot am I looking at?

I stumbled on to these following two slides (slides 21 & 22 on a machine learning tutorial found here): The first is obviously an $x,y$ scatterplot of height and weight. But what is the ...