def kernel(rvs, idx):
rvs, _ = fun_mcmc.running_covariance_step(
rvs, data[idx], window_size=window_size)
return (rvs, idx + 1), (rvs.mean, rvs.covariance)
def kernel(rcs, idx):
rcs, _ = fun_mcmc.running_covariance_step(
rcs, data[idx], axis=aggregation)
return (rcs, idx + 1), ()