def METHOD_NAME():
    prior = JointIndependent(marginals=[Uniform(loc=-2.0, scale=4.0), Uniform(loc=-2.0, scale=4.0)])
    sampler = MetropolisHastings(dimension=2, n_chains=20)
    test = SequentialTemperingMCMC(pdf_intermediate=likelihood,
                                   resampling_proposal=MultivariateNormal(mean=np.zeros(2), cov=1.0),
                                   distribution_reference=prior,
                                   percentage_resampling=10,
                                   sampler=sampler,
                                   nsamples=100,
                                   random_state=960242069)
    assert np.round(test.evaluate_normalization_constant(), 4) == 0.0437