منابع مشابه
Time series analysis - univariate and multivariate methods
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Canonical correlation analysis has been widely used in the literature to identify the underlying structure of a multivariate linear time series. Most of the studies assume that the innovations to the multivariate system are Gaussian. On the other hand, there are many applications in which the normality assumption is either questionable or clearly inadequate. For example, most empirical time ser...
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This paper reviews the applications of classical multivariate techniques for discrimination, clustering and dimension reduction for time series data. It is shown that the discrimination problem can be seen as a model selection problem. Some of the results obtained in the time domain are reviewed. Clustering time series requires the deÞnition of an adequate metric between univariate time series ...
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SUMMARY The development of adequate models for binary time series data with covariate adjustment has been an active research area in the last years. In the case, where interest is focused on marginal and association parameters, generalized estimating equations (GEE) (see for example Lipsitz, Laird and Harrington (1991) and Liang, Zeger and Qaqish (1992)) and likelihood (see for example Fitzmaur...
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When dealing with multivariate time series an important question one may ask is whether the measured signals are independent or not. Any interrelation can, for example, provide information about the underlying physical mechanisms or may be used to exploit possible redundancy in order to reduce the number of measurement channels. In linear systems theory the standard tool for detecting dependenc...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 1973
ISSN: 0047-259X
DOI: 10.1016/0047-259x(73)90029-8