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演示平稳化思想，完整项目中可替换为 statsmodels ARIMA。
一维时间序列。
下一期点预测。
交通指数、价格。
完整可运行代码
import numpy as np
series = np.array([21, 23, 24, 28, 30, 31, 34, 36], dtype=float)
diff = np.diff(series)
# 极简 AR(1)：diff_t = c + phi * diff_{t-1}
x, y = diff[:-1], diff[1:]
phi = np.cov(x, y, bias=True)[0, 1] / np.var(x)
c = y.mean() - phi * x.mean()
next_diff = c + phi * diff[-1]
print("下一期预测:", series[-1] + next_diff)