class_docstr: Diagnostic and specification tests and plots for Count model
  
  status: experimental
  
  Parameters
  ----------
  results : Results instance of a count model.
  y_max : int
      Largest count to include when computing predicted probabilities for
      counts. Default is the largest observed count.
code: def probs_predicted(self):
      if self.y_max is not None:
          kwds = {"y_values": np.arange(self.y_max + 1)}
      else:
          kwds = {}
      return self.results.predict(which="prob", **kwds)
  
file_path: statsmodels/statsmodels/discrete/diagnostic.py
imports: import warnings
  import numpy
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.stats.diagnostic_gen import test_chisquare_binning
  from statsmodels.discrete._diagnostics_count import test_poisson_dispersion, test_poisson_zeroinflation_jh, test_poisson_zeroinflation_broek, test_poisson_zeros, test_chisquare_prob, plot_probs
label_desc: Use image node_id 2 for calling the CountDiagnostic obj's underlying member method code with example usage: obj.probs_predicted() and returns: self