Simulation of multivariate non-gaussian autoregressive time series with given autocovariance and marginals

被引:4
|
作者
Kugiumtzis, Dimitris [1 ]
Bora-Senta, Efthimia [2 ]
机构
[1] Aristotle Univ Thessaloniki, Fac Engn, Dept Elect & Comp Engn, Thessaloniki 54124, Greece
[2] Aristotle Univ Thessaloniki, Dept Math, Thessaloniki 54124, Greece
关键词
Autocorrelation; Gaussian time series; Non-Gaussian time series; Stochastic simulation; Randomization test; SURROGATE-DATA; SPECIFIED MARGINALS; MAGNETOSPHERIC DATA; NONLINEAR-ANALYSIS; INPUT PROCESSES; RANDOM VECTORS; DISTRIBUTIONS; MODELS; GENERATION; NUMBERS;
D O I
10.1016/j.simpat.2014.03.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A semi-analytic method is proposed for the generation of realizations of a multivariate process of a given linear correlation structure and marginal distribution. This is an extension of a similar method for univariate processes, transforming the autocorrelation of the non-Gaussian process to that of a Gaussian process based on a piece-wise linear marginal transform from non-Gaussian to Gaussian marginal. The extension to multivariate processes involves the derivation of the autocorrelation matrix from the marginal transforms, which determines the generating vector autoregressive process. The effectiveness of the approach is demonstrated on systems designed under different scenarios of autocovariance and marginals. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:42 / 53
页数:12
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