code: def calcTBATSFaster(y_trans, w_transpose, g, F, x_nought):
      n = y_trans.shape[0]
  
      yhat = np.zeros((1, n))
      e = np.zeros((1, n))
      x = np.zeros((n, len(x_nought)))
  
      yhat[0, 0] = np.dot(w_transpose[0], x_nought)
      e[0, 0] = y_trans[0] - yhat[0, 0]
      x[0] = np.dot(F, x_nought) + (g[:, 0] * e[0, 0])
  
      for j in range(1, y_trans.shape[0]):
          yhat[:, j] = np.dot(w_transpose[0], x[j - 1])
          e[0, j] = y_trans[j] - yhat[0, j]
          x[j] = np.dot(F, x[j - 1]) + g[:, 0] * e[0, j]
  
      return yhat, e, 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 8 for calling a global function with example usage: calcTBATSFaster(y_trans, w_transpose, g, F, x_nought) and returns: yhat,  e,  x