三者是一致的,单整是指不平稳序列,为了平稳需要差分,但为了预测,又必须反过来求和才能预测原始的序列,否则预测的是差分后的序列.由此可见三者的确是从不同角度来称谓的.关于差分阶数,一般是一次次摸索进行,不过一般不超过2次,有时需要普通差分,有时需要季节差分,普通差分一般是一阶差分,季节差分往往是高阶的,例如月度数据为12阶,季度数据为4阶.

2# harlon1976 我们有记错的话，季节因素应该是由步差来解决的吧，进行几阶差分的目的是为了消除趋势效应，之后用步差来消除季节效应吧

考虑2阶差分后的方差，如果与1阶差分相比，变大的话，就说明是过差分，好像是这个样子

谢谢楼上两位的解答。个人觉得harlon1976 老兄说的季节差分有些问题，月度差分应该还是12步差分，而不是12阶；呵呵。。。关于过差分，在SAS帮助文件中有这么一段话，理解得不是很清楚明白，拿到这来请大家讨论评述：
    “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.
      望各路高手出手帮助！！

我没有看到用步衡量的,我说的12阶差分和你的意思是一致的,为Xt-(Xt-12).