code: def _parzen(u):
      z = np.where(
          np.abs(u) <= 0.5,
          4.0 / 3 - 8.0 * u**2 + 8.0 * np.abs(u) ** 3,
          8.0 * (1 - np.abs(u)) ** 3 / 3.0,
      )
      z[np.abs(u) > 1] = 0
      return z
  
imports: import numpy
  import warnings
  import scipy.stats
  from numpy.linalg import pinv
  from scipy.stats import norm
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.regression.linear_model import RegressionModel, RegressionResults, RegressionResultsWrapper
  from statsmodels.tools.sm_exceptions import ConvergenceWarning, IterationLimitWarning
label_desc: Use image node_id 1 for calling a global function with example usage: _parzen(u) and returns: z