Posterior inference for multivariate regression

The 10,000 iteration RJAGS simulation output, rail_sim_2, is in your workspace along with a data frame of the Markov chain output:

> head(rail_chains_2, 2)
         a b.1.      b.2.        c         s
1 49.76954    0 -12.62112 4.999202 111.02247
2 30.22211    0  -3.16221 4.853491  98.11892

You will use these 10,000 unique sets of parameter values to summarize the posterior mean trend in the relationships between trail volume, weekday status, and hightemp.

Construct a scatterplot of volume by hightemp.

Use color to distinguish between weekdays & weekends.
Superimpose a red line that represents the posterior mean trend of the linear relationship between volume and hightemp for weekends: m = a + c Z
Superimpose a turquoise3 line that represents the posterior mean trend of the linear relationship between volume and hightemp for weekdays: m = (a + b.2.) + c Z

Exercise

Posterior inference for multivariate regression

Instructions