log.lin.mod_brms.R

log.lin.mod
##  Family: gaussian (identity) 
## Formula: log_units ~ temp 
##    Data: NULL (Number of observations: 12) 
## Samples: 2 chains, each with n.iter = 2000; n.warmup = 500; n.thin = 1; 
##          total post-warmup samples = 3000
##    WAIC: -9.76
##  
## Fixed Effects: 
##           Estimate Est.Error l-95% CI u-95% CI Eff.Sample Rhat
## Intercept     4.41      0.23     3.97     4.92        541    1
## temp          0.08      0.01     0.06     0.11        549    1
## 
## Family Specific Parameters: 
##                  Estimate Est.Error l-95% CI u-95% CI Eff.Sample Rhat
## sigma(log_units)     0.16      0.04      0.1     0.25        639    1
## 
## Samples were drawn using NUTS(diag_e). For each parameter, Eff.Sample is a 
## crude measure of effective sample size, and Rhat is the potential scale 
## reduction factor on split chains (at convergence, Rhat = 1).
plot(log.lin.mod)