# Questions tagged [hierarchical-bayesian]

Hierarchical Bayesian models specify priors on parameters and hyperpriors on the parameters of the prior distributions

566 questions
Filter by
Sorted by
Tagged with
7 views

### Signs of estimated coefficients using Bayesian Poisson regression and Hierarchical Poisson regression

For poisson regression, I used the formula Y~ v1+ v2+ v3+ v1$*$v2+ v1$*$v3+ v2$*$v3, i.e. the main effects plus the interaction terms. I have used Metropolis algorithm and variable selection on the ...
8 views

### Analyzing the variance of an outcome variable: modelling standard deviation/sigma itself

Is the following a correct approach for sigma modelling? Let’s assume we have a Y variable named hours in lognormal scale. We would like to know how these hours changed in time (variable named year). ...
8 views

### Transforming log-scaled splines regression outputs to an understandable scale

Please give me some advice. I am using brms package and mgcv package for two regression models: bernoulli lognormal The problem is that both of these models outputs are in lognormal scale. As much ...
48 views

### Accounting for multiple layers of uncertainty in a model

Let's say I have data on 10 stores that sell widgets, each of which received num_orders number of orders in a certain timeframe, and sold a total of ...
7 views

### May Skilling's Nested Sampling Estimate parameters in hierarchical model?

May Skilling's Nested Sampling integration technique Estimate parameters in hierarchical model?
16 views

### Lognormal model: reporting median or geometric mean

I have a bayesian lognormal model as follows (brms package): m = brm(y ~ 1, data = df, family = lognormal) Model was run with default priors. This is model's ...
40 views

### R Stan: Rejecting initial value error only with real data, not with simulated data

I am trying to fit a non-linear function to a dataset using Stan and R. I tested my model with a simulated dataset. It works nicely. However, as soon as I use real data that is formatted exactly the ...
10 views

### Bayesian Hierarchical Models with different group sizes of crossed random effects

I have some abundance data for sites taken over a series of years. Some sites are missing data for some years and some sites only started being recorded several years in. I'm interested in the factors ...
18 views

7 views

### Group level distribution for positive parameters in Bayesian multilevel models

I am doing a lot of modeling with models that require some parameters to be positive by design. However, I am struggling to figure out which approach works best when I try to use multilevel modeling ...
49 views

### Exploding probability under simple hierarchical Bayesian formulation

I am wondering if someone here can clear up a point of confusion that I have when applying MCMC or an optimization method to hierarchical Bayesian problems. Let's say we have a likelihood and prior ...
12 views

### How to obtain equation for evidence given equation for joint density of latent and observed variables (Variational Inference)

I am working through the following review paper: https://arxiv.org/pdf/1601.00670.pdf and would like to gain some insight into arriving at the formulae for joint density of latent and observed ...
8 views

### Ideas how to report/emphasize a non-linear effect in abstract as text in case of no p-values?

I have a result that needs to be noted in abstract as this is important. I use Bayesian regression modelling and I have non-linear? effects as shown on plots below, what is a good way for reporting it ...
48 views

### One-step ahead predicitons in a Bayesian state-space model

How can I make one-step ahead predictions in a Bayesian state-space model? Specifically, for the model \begin{align} y_t \sim& N(x_t, py) \\ x_t \sim& N(rx_{t-1}, px) \end{align} where $y_t$ ...