Interpreting categorical coefficients
In your Bayesian model, \(m\)i \(= a + b X\)i specified the dependence of typical trail volume on weekday status \(X\)i (1 for weekdays and 0 for weekends). A summary()
of your RJAGS model simulation provides posterior mean estimates of parameters \(a\) and \(b\), the latter corresponding to b.2.
here.
> summary(rail_sim_1)
Mean SD Naive SE Time-series SE
a 428.47 23.052 0.23052 0.5321
b.1. 0.00 0.000 0.00000 0.0000
b.2. -77.78 27.900 0.27900 0.6422
s 124.25 9.662 0.09662 0.1335
Which of the following is the best interpretation of these posterior summaries?
This exercise is part of the course
Bayesian Modeling with RJAGS
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