def ConvCnstrMOD(*args, **kwargs):
    """A wrapper function that dynamically defines a class derived from
    one of the implementations of the Convolutional Constrained MOD
    problems, and returns an object instantiated with the provided
    parameters. The wrapper is designed to allow the appropriate
    object to be created by calling this function using the same
    syntax as would be used if it were a class. The specific
    implementation is selected by use of an additional keyword
    argument 'method'. Valid values are:

    - ``'ism'`` :
      Use the implementation defined in :class:`.ConvCnstrMOD_IterSM`. This
      method works well for a small number of training images, but is very
      slow for larger training sets.
    - ``'cg'`` :
      Use the implementation defined in :class:`.ConvCnstrMOD_CG`. This
      method is slower than ``'ism'`` for small training sets, but has better
      run time scaling as the training set grows.
    - ``'cns'`` :
      Use the implementation defined in :class:`.ConvCnstrMOD_Consensus`.
      This method is the best choice for large training sets.

    The default value is ``'cns'``.
    """

    # Extract method selection argument or set default
    if 'method' in kwargs:
        method = kwargs['method']
        del kwargs['method']
    else:
        method = 'cns'

    # Assign base class depending on method selection argument
    if method == 'ism':
        base = ConvCnstrMOD_IterSM
    elif method == 'cg':
        base = ConvCnstrMOD_CG
    elif method == 'cns':
        base = ConvCnstrMOD_Consensus
    else:
        raise ValueError('Unknown ConvCnstrMOD solver method %s' % method)

    # Nested class with dynamically determined inheritance
    class ConvCnstrMOD(base):
        def __init__(self, *args, **kwargs):
            super(ConvCnstrMOD, self).__init__(*args, **kwargs)

    # Allow pickling of objects of type ConvCnstrMOD
    _fix_dynamic_class_lookup(ConvCnstrMOD, method)

    # Return object of the nested class type
    return ConvCnstrMOD(*args, **kwargs)