Regards,

I am trying to create a *Bayesian Linear Regression* model with one independent variable. However, when I try to sample my model using the NUTS sampler, I get the following error: “Sampling Error: Bad Initial Energy”.

The code below shows the approach I followed to build my model:

```
basic_model = pm.Model()
with basic_model:
alpha = pm.Gamma('alpha', mu=alpha_mean, sigma=alpha_std, shape=(1))
beta = pm.Beta('beta', mu=beta_mean, sigma=beta_std, shape=(1))
sigma = pm.HalfNormal('sigma', tau=1)
mu = alpha + beta*model_input
Y_obs = pm.Beta('Y_obs', mu=mu, sigma=sigma, observed=model_output)
```

`with basic_model:`

```
trace = pm.sample(500, cores=1, init='adapt_diag')
```

I had pre-calculated the inputs to the model as follows:

```
# Slice out Variables
X = bayesian_regressor_frame['X']
Y = bayesian_regressor_frame['Y']
X = X.values
Y = Y.values
model_input = theano.shared(X)
model_output = theano.shared(Y)
# Calculate Parameters
alpha_mean = Rolling_OLS_params['alpha'].mean()
alpha_std = Rolling_OLS_params['alpha'].std()
beta_mean = Rolling_OLS_params['beta'].mean()
beta_std = Rolling_OLS_params['beta'].std()
```

I have taken the liberty to attach the input files that were used to build the model. Where am I going wrong?

bayesian_regressor_frame.csv (113.2 KB) Rolling_OLS_params.csv (102.8 KB)