class_docstr: A class representing a collection of discrete distributions.
  
  Parameters
  ----------
  xk : 2d array_like
      The support points, should be non-decreasing within each
      row.
  pk : 2d array_like
      The probabilities, should sum to one within each row.
  
  Notes
  -----
  Each row of `xk`, and the corresponding row of `pk` describe a
  discrete distribution.
  
  `xk` and `pk` should both be two-dimensional ndarrays.  Each row
  of `pk` should sum to 1.
  
  This class is used as a substitute for scipy.distributions.
  rv_discrete, since that class does not allow non-integer support
  points, or vectorized operations.
  
  Only a limited number of methods are implemented here compared to
  the other scipy distribution classes.
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code: def __init__(self, xk, pk):
      self.xk = xk
      self.pk = pk
      self.cpk = np.cumsum(self.pk, axis=1)
  
imports: import numpy
  from statsmodels.base import model
  import statsmodels.base.model
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.compat.pandas import Appender
label_desc: Use image node_id 1 to create a new rv_discrete_float object  with example: obj = rv_discrete_float(xk, pk)