statisticalrethinkin..

13.2. MULTILEVEL TADPOLES 341is model fit provides estimates for 50 parameters: one overall sample intercept α, the varianceamong tanks σ, and then 48 per-tank intercepts α j . Let’s check DIC though to see theeffective number of parameters:DIC(m13.1)R code13.2[1] 212.0444attr(,"pD")[1] 40.26574Only 40 effective parameters. ere are 10 fewer effective parameters than actual parameters,because the prior assigned to each α j shrinks them all towards zero. In this case, the prior isreasonably strong. Check the average value of sigma_tank with precis or coef and you’llsee it’s around 1.6. So each α j is assigned a Gaussian prior with mean zero and standarddeviation 1.6. is is a REGULARIZING PRIOR, like you’ve used in previous chapters, butnow the amount of regularization has been learned from the data itself.You can plot the median per-tank estimates with:post