最近在用arima建模，对过差分的判断据我说知有两种方法：第一，若差分后序列的方差反而变大，说明存在过差分；第二通过逆自相关函数图判断。为此sas9.1.3帮助文件里有这么一段话：
“The sample inverse autocorrelation function (SIACF) plays much the same role in ARIMA modeling as the sample partial autocorrelation function (SPACF) but generally indicates subset and seasonal autoregressive models better than the SPACF.
        Additionally, the SIACF may be useful for detecting over-differencing. If the data come from a nonstationary or nearly nonstationary model, the SIACF has the characteristics of a noninvertible moving average. Likewise, if the data come from a model with a noninvertible moving average, then the SIACF has nonstationary characteristics and, therefore, decays slowly. In particular, if the data have been over-differenced, the SIACF looks like a SACF from a nonstationary process.

      看得我似懂非懂，有哪位能给翻译或者解释一下，劳驾！！