python - ValueError : The computed initial MA coefficients are not invertible You should induce invertibility

我正在做一个时间序列问题。当我做AR模型时，一切都正确。

# Import the module for estimating an ARMA model
from statsmodels.tsa.arima_model import ARMA

# Fit the data to an AR(p) for p = 0,...,6 , and save the BIC
BIC = np.zeros(7)
for p in range(7):
    mod = ARMA(data, order=(p,0))
    res = mod.fit()
# Save BIC for AR(p)
    BIC[p] = res.bic

# Plot the BIC as a function of p
plt.plot(range(1,7), BIC[1:7], marker='o')
plt.xlabel('Order of AR Model')
plt.ylabel('Bayesian Information Criterion')
plt.show()

但是，当我在做MA模型时:

# Fit the data to an MA(q) for q = 0,...,6 , and save the BIC
BIC = np.zeros(7)
for q in range(7):

    mod = ARMA(data, order=(0,q))
    res = mod.fit()
# Save BIC for MA(q)
    BIC[q] = res.bic


# Plot the BIC as a function of p
plt.plot(range(1,7), BIC[1:7], marker='o')
plt.xlabel('Order of MA Model')
plt.ylabel('Bayesian Information Criterion')
plt.show()

我会得到:

ValueError: The computed initial MA coefficients are not invertible
You should induce invertibility, choose a different model order, or you can
pass your own start_params.

阅读non Invertible of a ARIMA model的答案后，我解决了错误:

# Fit the data to an MA(q) for q = 0,...,6 , and save the BIC
BIC = np.zeros(7)
for q in range(7):
    try:
        mod = ARMA(data, order=(0,q))
        res = mod.fit()
# Save BIC for MA(q)
        BIC[q] = res.bic
    except:
        pass

# Plot the BIC as a function of p
plt.plot(range(1,7), BIC[1:7], marker='o')
plt.xlabel('Order of MA Model')
plt.ylabel('Bayesian Information Criterion')
plt.show()

但是，我真的不明白为什么可以解决它，这就是为什么我想问这个问题。可能有人给出完整的答案。

最佳答案

在尝试为ARIMA(p，d，q)模型找到可逆问题的解决方案时，我在这里跌跌撞撞。我不太确定这是否适用于您的情况，但是我以尝试输入d = 0的方式找到了解决方案。而我已经将一阶差分应用于输入ts以使序列平稳。所以当我把d = 1时，可逆性问题就解决了。

希望这个对你有帮助。
谢谢。

关于python - ValueError : The computed initial MA coefficients are not invertible You should induce invertibility，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/52815990/