All Questions
18
questions
1
vote
0
answers
48
views
Power of Bernoulli likelihood in Jags (R2jags) [closed]
In a fixed power prior model, the model is set up as:
$$ \pi(p_i \mid \alpha,\mathcal{D}_0) \propto L(p_i\mid \mathcal{D}_0)^{w} \pi(p_i) $$
Suppose that the event follows a Bernoulli distribution ...
- 21
0
votes
0
answers
25
views
Data-informed grouping of covariates in Bayesian Hierarchical Modeling?
Is there a way to place a prior on the first stage's betas that allows the second stage groups to be determined from the data? I am working with co-exposures where I am not super confident in how they ...
- 13
1
vote
1
answer
226
views
In JAGS, how can I fix a parameter to a distribution, as opposed to just a constant?
The first code chunk below (model1) is a JAGS script designed to estimate a two-group Gaussian mixture model with unequal variances. I am looking for a way to fix one of the parameters (say $\mu_2$) ...
- 2,856
0
votes
1
answer
130
views
Distributions with negative support in JAGS
I am creating a Bayesian regression model where I want to include a prior for a variable that can only have a negative coefficient. What distribution can I use that only has a negative support and is ...
- 101
1
vote
1
answer
184
views
What prior distribution of parameters in the Bayesian estimation of a GARCH model?
In the case of the Bayesian estimation of GARCH(1, 1) model with Student–t or a Skewed distributions for innovations, is it more correct to assume a uniform distribution for the parameters or to ...
- 97
1
vote
1
answer
146
views
How to include Cohen's D from Meta-Analysis into JAGS/BUGS mean difference model
I was wondering if anyone knew of a way to use Cohen's D (and Standard Error) as an informed prior while building a BUGS model (to be tested in JAGS through R) that compares the mean difference ...
- 416
4
votes
1
answer
2k
views
Priors for Truncated Parameters - RJAGS
I would like to estimate the parameters of a specific model.
The model specification is as follows:
$p_t = k_t + B_t/(1-B_t) + \eta_t$, where $ \eta_t \sim N(0, \sigma^2)$
$R_{t+1} = R_{t} + R_t (...
- 993
2
votes
1
answer
5k
views
Gamma parameterization and how to randomly generate $\sigma$'s for use in `rnorm(n, $\mu$, $\sigma$)`
Say I have a normal distribution parameterized with a mean ($\mu$) and precision ($\tau = 1/\sigma^2)$. In JAGS, I would specify a prior for $\tau$ as ...
- 958
5
votes
0
answers
468
views
AR(1) model - which prior to use?
I want to use the following univariate model:
$y_t = \mu_t + \epsilon_t, \ \epsilon_t \sim N(0,1)$
$\mu_t = \phi \mu_{t-1} + \omega_t, \ \omega_t \sim N(0,\sigma_\omega^2)$
That is, $\mu_t$ follows ...
- 993
5
votes
1
answer
514
views
Estimating von Mises Parameters for Angular Data
I want to model some angular data.
Any input on how to incorporate the von Mises distribution and suggestions on appropriate priors in RJAGS for von Mises mean and concentration would be greatly ...
- 103
9
votes
0
answers
3k
views
Hyper-prior for negative binomial in hierarchical model using JAGS/BUGS
Below I'm using a negative binomial because it is more flexible than a simple poisson model. The data are counts $y$ of events for 16 individuals $x$. There are 14 counts (i.e. counting periods) for ...
- 1,119
5
votes
1
answer
1k
views
Use the improper prior $p(v) \propto 1/v$ into Jags
I know that one can approximate this density ($p(v) \propto 1/v$) using its truncated version and implement it this way:
...
- 5,063
7
votes
1
answer
6k
views
How to specify the Wishart distribution scale matrix
I'm running the below Bayesian mixing model in R using the rjags package, but I am having difficultly in specifying the scale matrix for the Wishart distribution. Essentially, I want Sigma.inv to be a ...
- 71
5
votes
1
answer
351
views
Difficulties with a Bayesian formulation of a model for human timing data
The Wing-Kristofferson model is a simple model of the behavior of a human trying to drum out a steady beat (that is, trying to mimic a metronome). Let $y_i$ be the $i$th interval between two drum ...
- 6,840
21
votes
2
answers
10k
views
What prior distributions could/should be used for the variance in a hierarchical bayesisan model when the mean variance is of interest?
In his widely cited paper Prior distributions for variance parameters in hierarchical models (916 citation so far on Google Scholar) Gelman proposes that good non-informative prior distributions for ...
- 6,840