class_docstr: distribution of success runs of length k or more (classical definition)
  
  The underlying process is assumed to be a sequence of Bernoulli trials
  of a given length n.
  
  not sure yet, how to interpret or use the distribution for runs
  of length k or more.
  
  Musseli also has longest success run, and waiting time distribution
  negative binomial of order k and geometric of order k
  
  need to compare with Godpole
  
  need a MonteCarlo function to do some quick tests before doing more
code: def pdf_nb(self, x, k, n, p):
      pass
  
imports: import numpy
  from scipy import stats
  from scipy.special import comb
  import warnings
  from statsmodels.tools.validation import array_like
label_desc: Use image node_id 2 for calling the RunsProb obj's underlying member method code with example usage: obj.pdf_nb(x, k, n, p) without return types