MODEL SELECTION AND ORDER DETERMINATION FOR TIME SERIES BY INFORMATION BETWEEN THE PAST AND THE FUTURE
作者:
Lei Li,
Zhongjie Xie,
期刊:
Journal of Time Series Analysis
(WILEY Available online 1996)
卷期:
Volume 17,
issue 1
页码: 65-84
ISSN:0143-9782
年代: 1996
DOI:10.1111/j.1467-9892.1996.tb00265.x
出版商: Blackwell Publishing Ltd
关键词: Time series;information;parametric models;order selection
数据来源: WILEY
摘要:
Abstract.In this paper, the information between the past and the future of a Gaussian stationary sequence is calculated either by its spectral density or by its autocovariances, and is related to the problem of model fitting. It is demonstrated that the criterion of minimum mutual information is the generalization of that of maximum entropy. By employing the above information quantity, we propose a procedure, which is called LIC for simplicity, to obtain consistent estimate of the order of the Bloomfield model or the autoregressive model. In Monte Carlo studies, we illustrate the LIC procedure by several examples, and also estimate the spectral density of time series by the Bloomfield model and LIC method.
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