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Chris Fonnesbeck fonnesbeck

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with pm.Model() as curve_spin_model:
spin = pm.Data('spin', curveball_data['spin_rate'])
β = pm.Normal('β', shape=2)
θ = β[0] + β[1]*(spin/1000)
swing_miss = pm.Data('swing_miss', curveball_data['miss'])
miss = pm.Bernoulli('miss', pm.invlogit(θ), observed=swing_miss)
df = pd.DataFrame(dict(y=np.array([2, 4, 2, 0, 4])))
with pm.Model() as glm:
x = np.array([0.3, 1.1, 0.6, -0.2, 3.3])
pm.glm.GLM.from_formula('y ~ x', data=df, family=pm.glm.families.Poisson())
more_curves = [1810, 2225, 3015]
with curve_spin_model:
pm.set_data({'spin': more_curves})
post_pred = pm.sample_posterior_predictive(trace, samples=1000)
traces = {}
for year in years:
with curve_spin_model:
year_data = curveball_data.query('year==@year')
pm.set_data({'spin': year_data.spin_rate,
'swing_miss': year_data.miss})
traces[year] = pm.sample(1000, tune=2000,
cores=2, progressbar=False)
@fonnesbeck
fonnesbeck / StudentT.ipynb
Created August 12, 2019 18:21
StudentT sampling
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