class_docstr: Fit height of signal peak over background.
code: def __init__(
      self,
      endog,
      exog=None,
      signal=None,
      background=None,
      *args,
      **kwargs,
  ):
      # assume we know the shape + location of the two components,
      # so we re-use their PDFs here
      self.signal = signal
      self.background = background
      super().__init__(
          endog=endog,
          exog=exog,
          *args,
          extra_params_names=self.exog_names,
          **kwargs,
      )
  
imports: import numpy
  from scipy import stats
  from statsmodels.base.model import GenericLikelihoodModel
  from numpy.testing import assert_array_less, assert_almost_equal, assert_allclose
label_desc: Use image node_id 1 to create a new TwoPeakLLHNoExog object from inherited base classes: GenericLikelihoodModel with example: obj = TwoPeakLLHNoExog(endog, exog, signal, background)