code: def checkAdmissibility(
      BoxCox_lambda,
      bc_lower_bound,
      bc_upper_bound,
      alpha,
      beta,
      phi,
      ar_coeffs,
      ma_coeffs,
      D,
  ):
      if BoxCox_lambda is not None:
          if (BoxCox_lambda < bc_lower_bound) or (
              BoxCox_lambda > bc_upper_bound
          ):
              return False
  
      if phi is not None:
          if (phi < 0.8) or (phi > 1):
              return False
  
      if ar_coeffs is not None:
          ar_lags = np.where(np.abs(ar_coeffs) > 1e-08)[0]
          if len(ar_lags) > 0:
              pval = max(ar_lags) + 1
              poly_coeffs = [1] + [-coef for coef in ar_coeffs[:pval]]
              roots = Polynomial(poly_coeffs).roots()
              if np.min(np.abs(roots)) < 1 + 1e-2:
                  return False
  
      if ma_coeffs is not None:
          ma_lags = np.where(np.abs(ma_coeffs) > 1e-08)[0]
          if len(ma_lags) > 0:
              qval = max(ma_lags) + 1
              poly_coeffs = [1] + list(ma_coeffs[:qval])
              roots = Polynomial(poly_coeffs).roots()
              if np.min(np.abs(roots)) < 1 + 1e-2:
                  return False
  
      D_eigen_values = scipy.linalg.eig(D, right=False)
  
      return np.all(abs(D_eigen_values) < 1 + 1e-2)
  
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 13 for calling a global function with example usage: checkAdmissibility(BoxCox_lambda, bc_lower_bound, bc_upper_bound, alpha, beta, phi, ar_coeffs, ma_coeffs, D) and returns: np, False, False, False, False