Dear all,
not long ago I started working with WinBUGS and within that espeacially
the car.proper model. I have a linear mixed model with random effects u
which are correlated and jointly normal distributed. So far I just
copy-pasted examples which looked like
u[1:k]~car.proper(mu[] ,C[] , adj[] ,num[] ,m[] , tau ,gamma)
gamma.min <- min.bound(C[], adj[], num[], m[])
gamma.max <- max.bound(C[], adj[], num[], m[])
gamma ~ dunif(gamma.min, gamma.max)
Like I understood the gamma represents the degree of spatial dependence.
I would like to estimate it. As a start I just took a mean of the
monitored gammas (I'm only monitoring the u's and gamma). This gave me
no good estimation. Since I am not that deep into the program my idea
was simply that this problem might be due to the uniform distribution.
Maybe a truncated normal with the latter gamma as mean might be a better
idea? I am thankful for any recommendation.
Best wishes
Beate Weidenhammer
--
Beate Weidenhammer
wiss. Mitarbeiterin
Freie Universität Berlin
Fachbereich Wirtschaftswissenschaft
Institut für Statistik und Ökonometrie
Lehrstuhl Rendtel
Garystr. 21 (Raum 325)
D-14195 Berlin
Tel.: +49 30 838-54203
Fax: +49 30 838-456629
email: [log in to unmask]
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