arima模型python代码

import pandas as pd

import numpy as np

from statsmodels.tsa.arima_model import ARIMA

import matplotlib.pyplot as plt

# 加载数据

data = pd.read_csv('your_data.csv', index_col='date', parse_dates=True)

# 拟合ARIMA模型

model = ARIMA(data, order=(1, 1, 1))

results = model.fit()

# 预测未来n个时间点的值

n = 10

forecast = results.forecast(steps=n)

# 绘制原始数据和预测结果

plt.plot(data, label='原始数据')

plt.plot(pd.date_range(start=data.index[-1], periods=n+1, freq=data.index.freq)[1:], forecast, label='预测结果')

plt.legend()

plt.show()

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