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3 votes
2 answers
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Parameterization of inverse gamma prior in Bayesian methods

For a prior of $\sigma^2 \sim IG(0.01, 0.01)$, often recommended as an uninformative prior for the variance parameter in MCMC approaches and other Bayesian methods, which parameterization does this ...
bob's user avatar
  • 755
1 vote
1 answer
774 views

Deriving posterior distribution for variance of normal distribution

I have a task to derive posterior distribution for parameter $\sigma^2$, given that the data vector $y^t = (y_1,...,y_t)$ is from $N(0,\sigma^2)$. The uninformative prior for $\sigma^2$ is $h(\sigma^2)...
PK1998's user avatar
  • 151
0 votes
0 answers
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how to determine a priori probability distribution of sigama2 in montecarlo simulation?

1、the monte carlo simulation code in SAS: Example1: https://support.sas.com/rnd/app/stat/examples/BayesStd/new_example/index.html ...
tumidou's user avatar
  • 75
1 vote
0 answers
141 views

Gamma likelihood with InverseGamma prior

I've got a gamma likelihood $\Gamma(\tau_c | \alpha_k, \frac{\alpha_k} {\tau_k})$ (parameterized with shape and rate) with an InverseGamma prior $IG(\tau_k|a_0, b_0)$. I know that the resulting ...
Lucivius's user avatar
0 votes
0 answers
109 views

Interpretation of priors in example

Suppose you have 3 variances $W_{1},W_{2},W_{3}$ that can be expressed as $W_{j}=q_{j}V$ with $j = 1,2,3$. According to one model, $W_{3}$ should be pronounced and $W_{1}$, $W_{2}$ should be small to ...
r_31415's user avatar
  • 3,361
3 votes
1 answer
3k views

Jeffreys prior for inverse gamma distribution

Does anybody have the experience of dealing with Jeffreys prior? I am working with hierarchical model at the moment where the parameter σ^2 from normal distribution is said to be chosen according to ...
Oleg's user avatar
  • 661