FITTING AUTOREGRESSIVE MODELS FOR PREDICTION
FITTING AUTOREGRESSIVE MODELS FOR PREDICTION
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DOI：
10.1007/bf02532251
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发表时间：
1969-01-01
影响因子：
1
通讯作者：
AKAIKE, H
中科院分区：
文献类型：
--
作者：
AKAIKE, H
这是一个新开发的简单和实用的程序的初步报告，用自回归模型统计识别预测。平稳时间序列的自回归表示（或创新方法）在时间序列分析中的应用最近引起了许多研究工作者的关注，人们期望这种时域方法能够解决许多问题，例如通过直接应用频域方法[1]，[2],[3]，[9]无法解决的噪声反馈系统的识别。
This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models. The use of autoregressive representation of a stationary time series (or the innovations approach) in the analysis of time series has recently been attracting attentions of many research workers and it is expected that this time domain approach will give answers to many problems, such as the identification of noisy feedback systems, which could not be solved by the direct application of frequency domain approach [1],[2],[3],[9].