code: def ar_coefficient(x, param=[{"coeff": 5, "k": 5}]):
      calculated_ar_params = {}
  
      x_as_list = list(x)
      calculated_AR = AR(x_as_list)
  
      res = {}
  
      for parameter_combination in param:
          k = parameter_combination["k"]
          p = parameter_combination["coeff"]
  
          column_name = "k_{}__coeff_{}".format(k, p)
  
          if k not in calculated_ar_params:
              try:
                  calculated_ar_params[k] = calculated_AR.fit(
                      maxlag=k, solver="mle"
                  ).params
              except (LinAlgError, ValueError):
                  calculated_ar_params[k] = [np.NaN] * k
  
          mod = calculated_ar_params[k]
  
          if p <= k:
              try:
                  res[column_name] = mod[p]
              except IndexError:
                  res[column_name] = 0
          else:
              res[column_name] = np.NaN
  
      return [(key, value) for key, value in res.items()]
  
imports: import pandas
  import numpy
  from statsmodels.tsa.stattools import acf, adfuller, pacf
  import itertools
  from statsmodels.tsa.ar_model import AR
  from scipy.signal import cwt, find_peaks_cwt, ricker, welch
  from scipy.stats import linregress
  import scipy.stats
  from scipy.stats import kurtosis
  from scipy.stats import skew
  import numpy
  from scipy import signal, integrate
  from scipy.interpolate import interp1d
  import math
  from statsmodels.tools.sm_exceptions import MissingDataError
  from numpy.linalg import LinAlgError
label_desc: Use image node_id 22 for calling a global function with example usage: ar_coefficient(x, param) and returns: unknown