Introducing a Constraint in the Leroux (besagproper2) Random Effects Model

[Marc]

Hello everyone,

We have implemented a huge model where several Leroux distribution (besagproper2) random effects have been included (https://inla.r-inla-download.org/r-inla.org/doc/latent/besagproper2.pdf)

To reduce the number of parameters to estimate, we would like to add the constraint in the model that all Lambda parameters from each of the Leroux distributions have the same value.

Is it possible to introduce this type of constraint with INLA?

Thank you very much!

Marc

[Håvard Rue]

yes, if the underlying graph is the same. is it ?

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Håvard Rue
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[Marc]

Yes, is the same graph.

[Helpdesk (Haavard Rue)]

thx. I'll send you an example tomorrow

he...@r-inla.org

[Helpdesk (Haavard Rue)]

can you check the example. the idea is to use two copies of the 'besagproper2'
model where the scaling in copy acts as the stdev (and the 'range=c(0,Inf)' will
do this in log-scale), hence lambda parameter is the same.

[Helpdesk (Haavard Rue)]

I think this should be done only if there is a good argument for all these
lambda's being the same.

On Mon, 2024-07-15 at 02:17 -0700, Marc wrote:

[Marc]

Thank you very much, Haavard! We will test the code and let you know if it worked for us. Best regards.

Marc