text: #  goes here
  b0 = np.linspace(0, 50, 101);
  b1 = np.linspace(-1, 1, 101);
  from itertools import product hypos = product(b0, b1)
  suite = Logistic(hypos);
  for data in zip(df.Temperature, df.Incident): print(data) suite.Update(data) goes here
  # Solution goes here
  Implement this model using MCMC. As a starting place, you can use this example from the PyMC3 docs.
  As a challege, try writing the model more explicitly, rather than using the GLM module.
  import pymc3 as pm
  # Solution goes here
  pm.traceplot(trace);
  The posterior distributions for these parameters should be similar to what we got with the grid algorithm.