Hello. Now, i'm writting thesis with the topic Small Area Estimation using Bayesian Approach. Models that i use in estimation are Linear Mixed Model (LMM) and Generalized Linear Mixed Model (GLMM) because my response variable is Zero-Inflated Data. But, i have problem when i fit a linear mixed model. I want specification prior for residual variance parameter (sigma^2) is 1/sigma^2 that i get using Jeffrey's Method from Normal distribution. So, how to specification that prior in MCMCglmm function? I hope you can help me. Thank you.
Specification Noninformative Prior with Jeffrey's Method in MCMCglmm function
2 messages · Euis Aqmaliyah, Jarrod Hadfield
Hi, I think p(sigma^2) = 1/sigma^2 is the limit of the inverse-chisquare distribution as nu goes to zero. This is the default in MCMCglmm. Cheers, Jarrod
On 26/03/2017 12:00, Euis Aqmaliyah wrote:
Hello. Now, i'm writting thesis with the topic Small Area Estimation using Bayesian Approach. Models that i use in estimation are Linear Mixed Model (LMM) and Generalized Linear Mixed Model (GLMM) because my response variable is Zero-Inflated Data. But, i have problem when i fit a linear mixed model. I want specification prior for residual variance parameter (sigma^2) is 1/sigma^2 that i get using Jeffrey's Method from Normal distribution. So, how to specification that prior in MCMCglmm function? I hope you can help me. Thank you. [[alternative HTML version deleted]]
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