# Questions tagged [uninformative-prior]

A prior that express lack of detailed information or lack of any information at all.

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### What is the advantage of running generalized mixed effect linear regression model with bayesian with non-informative prior vs frequentist approach?

I am curious as to whether the bayesian approach with non-informative prior (flat prior) is more suitable for generalized mixed effects linear model than frequentist approach and what the reasons may ...
1 vote
39 views

### In Bayesian modelling how to interpret hierarchical hyperparameters with regards to "borrowing"?

With regards to hierarchical models I often see these referred to as groups borrowing information from each other e.g. It will be seen that the hierarchical model posterior estimates for one school ...
56 views

### What is the right Haar prior for the Weibull distribution?

From Wikipedia, the Weibull distribution is defined with the exceedance distribution function (aka survival function) $\exp[-(x/\lambda)^k]$. If I transform the random variable $x$ using $x'=ax^b$ ...
1 vote
54 views

### Informative priors for Bayesian chi-squared test

A colleague recently presented results from a chi-squared test that used a Bayesian method for estimation. The results seemed promising, but when I looked up the main function ...
71 views

### How can I solve identifiability problems in my STAN estimation?

So I am trying to validate my STAN model before using real data and am having some trouble estimating parameters separately. My data structure contains count data with people on the rows, and test ...
28 views

### Distribution families whose likelihoods integrate to $+\infty$ for some sample values

I've recently started learning about Bayesian statistics, and I came across this very nice answer by Xi'an https://stats.stackexchange.com/a/129908/268693, which [in my slight paraphrasing] says the ...
34 views

1 vote
90 views

### Is there any strong argument about objective/non-informative improper prior?

Decades ago improper objective priors - e.g. $\pi(\sigma) \propto \sigma^{-1}, \sigma > 0,$ for a scale parameter - were considered problematic because some authors thought they were leading to the ...
27 views

### Non-informative prior of a geometric distribution [duplicate]

If we are given a standard geometric distribution $(1-p)^{x-1} p$, with $0<p<1$ what would be a suitable non-informative prior for this?
853 views

### Informative priors for standard deviation (or variance)

Suppose I want to perform Bayesian estimation of the mean $\mu$ and standard deviation $\sigma$ of a Gaussian distribution. Is there a standard way to specify an informative prior over $\sigma$, ...
1k views

### In Bayesian models, can you use Uniform(-inf, inf) as a prior?

In Bayesian models, can you use Uniform(-inf, inf) as a prior? I ask because in an class, we looked at MH MCMC sampler, and showed that to sample from a distribution, we need not explicitly solve for ...
1 vote
82 views

### Literature on Noninformative Priors for GPD

I am starting to do some work using the Generalized Pareto Distribution (GPD), and was hoping someone might be able to point me in the direction of literature (or just general recommendations) on ...
502 views

### Is it really worth doing Bayesian Analysis if you have no idea about Priors? [duplicate]

I have heard that if you use uniform priors in Bayesian Analysis, it is the same as doing Frequentist Analysis. If you are creating statistical models and you really have no idea about the prior ...
29 views

### Are there any uninformative priors with an unlimited support like $(-\infty,\infty), (0,\infty), (-\infty,0)$? [duplicate]

The Bayes theorem is: $P(\theta | x)=\displaystyle \frac{p(\theta)L_x(\theta)}{\int_{\theta \in A}p(\theta)L_x(\theta)d\theta}$ It's pretty clear that $\theta's$ support will not change as bayes ...
235 views

### Analytical expression of the log-likelihood of the Binomial model with unknown $n$ and known $y$ and $p$ and its conjugate prior

I'm trying to derive the MLE and Bayesian posterior for $n$ in the Binomial model, $\mathrm{Binomial}(n, p)$ with known $y$ and $p$. The following questions arise How to derive analytically the ...
115 views

### Batches of bayesian updates for gaussian with unknown variance different from computation with all data

I'm working on a project where I continuously (in batches) update the pdf estimation for an event normally distributed. My variance is unknown, so I'm using the equations given in session 4.1.2 of ...
1 vote
3k views

### How does one place an uninformative prior on a Gamma Distribution?

I'd like to choose an uninformative prior for the scale and shape parameters of the Gamma distribution. Any help and suggestions will be appreciated.
1 vote
979 views

### Why is Cauchy the default prior for both testing and estimation?

Assume that a data set follows a normal distribution and the prior and posterior both have a normal-gamma distribution. When we are performing Bayesian analysis but don't want any subjective choice of ...
116 views

### Numbers of draws on a modified Bernouilli process

Here is the setup: Bob runs an experiment: he flips a coin N times (between 0 and +$\infty$). The coin has a probability p of landing on heads. Bob starts with zero points. For each head, Bob scores a ...
1 vote
34 views

### When can a winner of the election be called: estimating population proportion without the assumption of random sampling

While following a recent election, I wanted to estimate population proportion of people who voted for a certain candidate knowing the sample proportion, sample size (and population size). I first ...
349 views

Can some one please help me out in Verifying if my prior distribution is uniform then will my Bayes estimate will always be MLE or UMVUE? If $X_i$ follow iid $N(\theta,1)$ and prior distribution of $\... 1 vote 1 answer 2k views ### Non-informative prior for Exponential I am working with a Bayesian model:$T \sim exp(\theta)$for survival data, I have chosen a gamma distribution as a prior since its conjugate by an exponential distribution. I'd like to choose a$\... 250 views

### Choosing reasonable priors for Poisson GLMM

I am using the package brms in R to fit a generalized linear mixed model using a Poisson distribution with log link. The model takes count data that ranges from 0 ...
2k views

### What is a non-informative choice of parameters for a Dirichlet distribution?

Dirichlet distribution is a conjugate prior for multinomial distribution. I want to impose a non-informative prior over sampling weights $\pi$ for a draw $x=(x_1,…,x_N)$ from a multinomial ...
183 views

### Uniform posterior on bounded space [duplicate]

In a particular Bayesian problem, I have encountered a choice of parameters that leads to a uniform posterior distribution. Given prior \begin{equation} p(\boldsymbol{\pi}) =Dirichlet(\boldsymbol{\...
482 views

### How to choose a non-informative or weakly informative hyper priors for my hierarchical bayesian model?

I am learning Bayes on "Applied Bayesian Statistics" by MK Cowles. The chapter about "Bayesian Hierarchical Models" mentioned an example that we estimate a softball player’s ...
2k views

### Why is this an example of a noninformative prior?

From Bayesian Data Analysis 3rd Edition [Gelman et. al], they give this as an example when introducing non-informative priors: "We return to the problem of estimating the mean θ of a normal ...
1 vote
645 views

### location/scale invariant priors

I'm trying to understand what's the motivation behind these priors, and why they are used. I understand that for location parameters of some distribution, you want it to be invariant of movement. e.g....
178 views

### Setting priors for bivariate regression

I would like to perform a bivariate MCMC regression with boldness scores as the continuous response variable, aggression ranks as the ordinal response variable, trial numbers as fixed effect and ...
830 views

### Choosing a ‘noninformative’ hyperprior distribution

I am trying to better understand hierarchical Bayesian models. I started here: https://blog.dominodatalab.com/ab-testing-with-hierarchical-models-in-python/ And ran into the following sentence ...
259 views

### Jeffreys prior vs. Flat prior on $(\beta,\log\sigma^2)$

I'm reading Bayesian Core, and the authors state that a Jeffreys prior $\pi(\beta,\sigma^2|X)\propto\frac{1}{\sigma^2}$ corresponds to a flat prior on $(\beta,\log\sigma^2)$. Why is this so?
216 views

### Can an improper prior distribution be informative?

I have just worked through an example where, with an improper prior, the bayesian estimator equals the maximum likelihood estimator, leading me to believe that improper priors are uninformative. But ...
1 vote
19 views

### Maximum entropy prior for dichotomous variables [closed]

I have a set of dichotomous variables $A, B, C,$... and I know their probabilities $P(A), P(B), P(C),$... as well es their pairwise dependencies $P(A \cap B), P(A \cap C), P(B \cap C),$... . Or in ...
1 vote
In a paper about the stochastic volatility, the author justifies his choice of prior distribution parameters $\pi(\mu) \sim \mathcal{N}(b_\mu,B_\mu) = \mathcal{N}(-9,0)$ of the level $\mu$ as follows: ...