def __init__(self, distribution, num_eigen=2, \ mean_est=array([-2.0, -2.0]), cov_est=0.05 * eye(2), \ sample_discard=500, sample_lag=10, accstar=0.234): AdaptiveMetropolis.__init__(self, distribution=distribution, \ mean_est=mean_est, cov_est=cov_est, \ sample_discard=sample_discard, sample_lag=sample_lag, accstar=accstar) assert (num_eigen <= distribution.dimension) self.num_eigen = num_eigen self.dwscale = self.globalscale * ones([self.num_eigen]) u, s, _ = svd(self.cov_est) self.eigvalues = s[0:self.num_eigen] self.eigvectors = u[:, 0:self.num_eigen]
def __init__(self, distribution, \ mean_est=None, cov_est=None, \ sample_discard=500, sample_lag=20, accstar=0.234): AdaptiveMetropolis.__init__(self, distribution, mean_est, cov_est, \ sample_discard, sample_lag, accstar)