标准误收敛

def solve():
    import numpy as np
    import statsmodels.api as sm
    import matplotlib.pyplot as plt
    
    np.random.seed(____)
    
    sample_sizes = [____, ____, ____, ____, ____, ____, ____, ____]
    standard_errors = []
    
    for n in sample_sizes:
        x = np.random.randn(____)
        y = ____ + ____*x + np.random.randn(____)
        X = sm.add_constant(____)
        se = sm.OLS(____).fit().bse[____]
        standard_errors.append(____)
    
    plt.figure(figsize=(____,____))
    plt.loglog(____)
    plt.loglog(sample_sizes, [standard_errors[____]/np.sqrt(____) for s in sample_sizes], 
               '____', linewidth=____, label='____')
    plt.title(____)
    plt.xlabel(____)
    plt.ylabel(____)
    plt.legend()
    plt.grid(____)
    plt.tight_layout()
    plt.show()
    
    def get_se(____):
        x = np.random.randn(____)
        y = ____ + ____*x + np.random.randn(____)
        X = sm.add_constant(____)
        return sm.OLS(____).fit().bse[____]
    se_100 = get_se(____)
    se_10000 = get_se(____)
    print(round(____))