sgld_student.py 文件源码

def gen(N, df, thinning=1):
    log_den = log_normal
    if df < np.Inf:
        log_den = grad_log_t_df(df)

    return metropolis_hastings(log_den, chain_size=N, thinning=thinning, x_prev=np.random.randn(), step=0.5)


# estimate size of thinning