Bayesian Weight Loss

1_Bayesian Weight Loss.md

Bayesian Weight Loss

bayesian.py

import pymc3 as pm

with pm.Model() as model_1:
    
    alpha = pm.Normal("alpha", mu=70, sigma=8)
    beta = pm.Normal("beta", mu=0, sigma=1)

    weight = pm.Deterministic("weight", alpha + beta * X)
    noise = pm.HalfNormal("noise", sigma=1)

    likelihood = pm.Normal("likelihood", mu=weight, sigma=noise, observed=Y)

    trace_1 = pm.sample(tune=1500)

ols.py

import statsmodels.api as sm

X_ols = sm.add_constant(X)

model = sm.OLS(Y, X_ols)

results = model.fit()
model.data.xnames = ["alpha", "beta"]
print(results.summary())

prob.py

print("Pr(Weight > 68) =", np.mean(alpha_samples + beta_samples * max(X) > 68))
# => Pr(Weight > 68) = 0.083