code: def makeXMatrix(b, s_vector, d_vector, epsilon_vector):
      # x = (l_t, b_t, s_vector, d_vector, epsilon_vector)
      x = np.array([0.0])
      if b is not None:
          x = np.append(x, b)
      if s_vector is not None:
          x = np.concatenate((x, s_vector))
      if d_vector is not None:
          x = np.concatenate((x, d_vector))
      if epsilon_vector is not None:
          x = np.concatenate((x, epsilon_vector))
  
      return x
  
imports: import warnings
  from functools import partial
  import numpy
  import pandas
  import scipy.linalg
  import statsmodels.api
  from numba import njit
  from numpy.polynomial.polynomial import Polynomial
  from scipy.special import inv_boxcox
  from scipy.stats import boxcox
  from scipy.optimize import minimize
  from statsmodels.tsa.stattools import adfuller
  from .arima import auto_arima_f
  from .utils import NOGIL, CACHE
label_desc: Use image node_id 3 for calling a global function with example usage: makeXMatrix(b, s_vector, d_vector, epsilon_vector) and returns: x