用r语言拟合平稳AR序列，并画出自相关图

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于 2021-10-14 19:41:10 发布

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文章标签： r语言 ar python

本文链接：https://blog.youkuaiyun.com/YTHAAA/article/details/120770849

本文介绍了如何使用r语言构建平稳的AR(Autoregressive)序列，并详细阐述了AR模型的原理，即利用前期的X值线性预测当前期的XT。同时，提到了该模型是线性回归的拓展，但这里的X预测X自身。还提及了VAR向量自回归模型作为AR模型的推广，与金融风险管理中的VAR模型区分开来。

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Autoregressive model is a statistical method to deal with time series. It uses the same variable, such as the previous periods of X, that is, X1 to xt-1, to predict the performance of XT in this period, and assumes that they are a linear relationship. Because this is developed from linear regression in regression analysis, but x is not used to predict y, but x is used to predict x (itself); So it’s called autoregression.
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Where: C is a constant term; It is assumed that the mean is equal to 0 and the standard deviation is equal to the random error value of; It is assumed to be constant for any t. The text description is: the expected value of X is equal to the linear combination of one or several late stages, plus constant term and random error.