code: def gen_data_for_model1():
      nobs = 1000
  
      rs = np.random.RandomState(seed=93572)
  
      d = 5
      var_y = 5
      var_coeff_x = 0.01
      var_coeff_w = 0.5
  
      x_t = rs.uniform(size=nobs)
      w_t = rs.uniform(size=nobs)
      eps = rs.normal(scale=var_y**0.5, size=nobs)
  
      beta_x = np.cumsum(rs.normal(size=nobs, scale=var_coeff_x**0.5))
      beta_w = np.cumsum(rs.normal(size=nobs, scale=var_coeff_w**0.5))
  
      y_t = d + beta_x * x_t + beta_w * w_t + eps
      return y_t, x_t, w_t, beta_x, beta_w
  
imports: from collections import OrderedDict
  import matplotlib.pyplot
  import numpy
  import pandas
  import statsmodels.api
  import pymc3
  import theano
  import theano.tensor
label_desc: Use image node_id 1 for calling a global function with example usage: gen_data_for_model1() and returns: y_t,  x_t,  w_t,  beta_x,  beta_w