Begin MCMC sampling: 
 
..... drawing sample # 100  after  0.02632895  minutes 
..... drawing sample # 200  after  0.0533181  minutes 
..... drawing sample # 300  after  0.0782951  minutes 
..... drawing sample # 400  after  0.1034765  minutes 
..... drawing sample # 500  after  0.1286169  minutes 
..... drawing sample # 600  after  0.1538991  minutes 
..... drawing sample # 700  after  0.1789224  minutes 
..... drawing sample # 800  after  0.2049654  minutes 
..... drawing sample # 900  after  0.2302492  minutes 
..... drawing sample # 1000  after  0.2551559  minutes 
..... drawing sample # 1100  after  0.280313  minutes 
Completed  1100  draws of MCMC algorithm 
Bayesian estimates of model parameters 
                    Mean    50%   2.5%  97.5%
beta.(Intercept)   0.052  0.076 -0.326  0.475
beta.veg           0.822  0.783  0.428  1.248
alpha.(Intercept)  0.771  0.776  0.583  0.965
alpha.sal         -0.371 -0.395 -0.536 -0.172
alpha.twg          0.051  0.050 -0.133  0.214
delta.(Intercept)  0.758  0.761  0.662  0.844
delta.sal         -0.482 -0.486 -0.604 -0.375
delta.fish        -0.239 -0.234 -0.362 -0.144
delta.turb         0.297  0.293  0.158  0.435

Monte Carlo SE of Bayesian estimates 
                    Mean    50%   2.5%  97.5%
beta.(Intercept)  0.0214 0.0273 0.0378 0.0416
beta.veg          0.0182 0.0292 0.0419 0.0356
alpha.(Intercept) 0.0100 0.0145 0.0195 0.0237
alpha.sal         0.0115 0.0135 0.0163 0.0128
alpha.twg         0.0096 0.0125 0.0341 0.0107
delta.(Intercept) 0.0042 0.0054 0.0111 0.0071
delta.sal         0.0059 0.0104 0.0126 0.0055
delta.fish        0.0075 0.0075 0.0134 0.0068
delta.turb        0.0054 0.0087 0.0108 0.0100
null device 
          1