Dear list members, I have run the ML and mcmc for my model. I am wondering if there is a simple transformation between the the ML coefficients and mcmc coefficients. Or in general how do I interpret the mcmc coefficients (I know how to interpret the ml coefficients). For example e^4.03 is not in the range of the HPD for beta1 of the mcmc nb1<-glmmadmb(D2_eggs~D2_female*(Bacteria+Enviro)+(1|Pop), data=data, family="nbinom1")
summary(nb1)
Call:
glmmadmb(formula = D2_eggs ~ D2_female * (Bacteria + Enviro) +
(1 | Pop), data = data, family = "nbinom1")
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.03120 0.26620 15.14 < 2e-16 ***
D2_female 0.05115 0.00532 9.62 < 2e-16 ***
BacteriaE 0.13913 0.25159 0.55 0.58
EnviroEC 1.06900 0.22090 4.84 1.3e-06 ***
D2_female:BacteriaE 0.02622 0.00578 4.54 5.7e-06 ***
D2_female:EnviroEC -0.03357 0.00471 -7.13 9.7e-13 ***
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Number of observations: total=95, Pop=16
Random effect variance(s):
Group=Pop
Variance StdDev
(Intercept) 0.04716 0.2172
Negative binomial dispersion parameter: 243.68 (std. err.: 48.422)
Log-likelihood: -572.814
nb_mcmc<-glmmadmb(D2_eggs~D2_female*(Bacteria+Enviro)+(1|Pop), data=data, family="nbinom1",mcmc=T, mcmc.opts=mcmcControl(mcmc=10000)) m<-as.mcmc(nb_mcmc$mcmc) head(HPDinterval(m))
lower upper beta.1 50.4190302 55.231164 beta.2 6.3920598 9.033473 beta.3 0.5165269 4.145737 beta.4 1.7327276 5.167999 beta.5 1.6289002 3.791544 beta.6 -3.9886068 -2.057463 Thanks Dean