title: Testing for correlation structures in short-term variabilities with long-term trends of multivariate time series.
abstract: We describe a method for identifying correlation structures in irregular fluctuations (short-term variabilities) of multivariate time series, even if they exhibit long-term trends. This method is based on the previously proposed small shuffle surrogate method. The null hypothesis addressed by this method is that there is no short-term correlation structure among data or that the irregular fluctuations are independent. The method is demonstrated for numerical data generated by known systems and applied to several experimental time series.
authors.affiliation: Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. entomo@eie.polyu.edu.hk
authors.forename: Tomomichi
authors.initials: T
authors.lastname: Nakamura
authors.forename: Yoshito
authors.initials: Y
authors.lastname: Hirata
authors.forename: Michael
authors.initials: M
authors.lastname: Small