class_docstr: Semiparametric partially linear model, ``Y = Xb + g(Z) + e``.
  
  Parameters
  ----------
  endog : array_like
      The dependent variable
  exog : array_like
      The linear component in the regression
  exog_nonparametric : array_like
      The nonparametric component in the regression
  var_type : str
      The type of the variables in the nonparametric component;
  
          - c: continuous
          - o: ordered
          - u: unordered
  
  k_linear : int
      The number of variables that comprise the linear component.
  
  Attributes
  ----------
  bw : array_like
      Bandwidths for the nonparametric component exog_nonparametric
  b : array_like
      Coefficients in the linear component
  nobs : int
      The number of observations.
  k_linear : int
      The number of variables that comprise the linear component.
  
  Methods
  -------
  fit
      Returns the fitted mean and marginal effects dy/dz
  
  Notes
  -----
  This model uses only the local constant regression estimator
  
  References
  ----------
  See chapter on Semiparametric Models in [1]
docstr: Provide something sane to print.
docstr_tok: ["Provide","something","sane","to","print","."]
code: def __repr__(self):
      """Provide something sane to print."""
      repr = "Semiparamatric Partially Linear Model \n"
      repr += "Number of variables: K = " + str(self.K) + "\n"
      repr += "Number of samples:   N = " + str(self.nobs) + "\n"
      repr += "Variable types:      " + self.var_type + "\n"
      repr += "BW selection method: cv_ls" + "\n"
      repr += "Estimator type: local constant" + "\n"
      return repr
  
imports: import numpy
  from scipy import optimize
  from scipy.stats.mstats import mquantiles
  from statsmodels.nonparametric.api import KDEMultivariate, KernelReg
  from statsmodels.nonparametric._kernel_base import gpke, LeaveOneOut, _get_type_pos, _adjust_shape
label_desc: Use image node_id 5 for calling the SemiLinear obj's underlying member method code with example usage: obj.__repr__() and returns: repr