Hi List and Jarrod.
I have a quick and simple question.
I am running a three variable additive MCMCglmm model  and my results are below.
My question is: how can I find out their relative importance in the model?

> summary(model17)

Iterations = 3001:12991
Thinning interval  = 10
Sample size  = 1000

DIC: 1465.078

G-structure:  ~spec

     post.mean l-95% CI u-95% CI eff.samp
spec      1365    319.9     1860    8.259

R-structure:  ~units

      post.mean l-95% CI u-95% CI eff.samp
units     206.6  0.04282     1200    11.92

Location effects: popcov ~ log(littersize) + latdd + dist_per

                                 post.mean    l-95% CI      u-95% CI     eff.samp  pMCMC
(Intercept)          46.71321        39.38765      53.35380     1000          <0.001 ***
log(littersize)     9.30711           1.98614        16.02647      906             0.010 *
latdd                     0.21497           0.05281        0.38508        1000           0.020 *
dist_per              24.97103         3.96583       44.23032      1000            0.008 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> posterior.mode(model17$Sol)
    (Intercept) log(littersize)           latdd        dist_per
     47.8320013       8.6668252       0.2491359      21.2098935
> #DIC: 3391.625
> HPDinterval(model17$VCV)
             lower    upper
spec  319.92091625 1860.361
units   0.04281968 1200.394
attr(,"Probability")
[1] 0.95
>


Navinder J Singh
Assistant Professor | Department of Wildlife, Fish, and Environmental Studies
Faculty of Forest Sciences | Swedish University of Agricultural Sciences
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