#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import pandas as pd
import pymc3 as pm
import seaborn as sns


# In[2]:


k = 1000
n = 100

fake_data = np.random.random((n, k+1))


# In[3]:


import theano.tensor as tt

with pm.Model() as model:
    
    y = fake_data[:, 0]
    X = fake_data[:, 1:]
    
    β = pm.Normal('β', 0, sd=10000, shape=k)
    σ = pm.Uniform('σ', 0, 1000)
    
    μ = tt.dot(X, β)
    
    likelihood = pm.Normal('likelihood', μ, sd=σ, observed=y)


# In[8]:


with model:
    tr = pm.sample(10000, step=pm.Metropolis())


# In[9]:


pm.summary(tr[-1000:])