By Hille E., Tamarkin J. D.
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1 INTRODUCTION In this chapter, we describe models for a vector time series Xt , with n components X1t , X2t , . . , Xnt , observed in times t = 0, ±1, ±2, . . Besides analyzing individual time series Xit , for which the autocorrelation contained in each series is important, we will be interested in dynamic relationships between the component series. We use the notation Xt = (X1t , X2t , .
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14 Multivariate Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Autoregressive Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Partial Causal Measures, PDC and dDTF . . . . . . . . . . . . . . . . . . . 19 Granger Causality and Its Relation to DTF . . . . . . . . . . . . . . . . . . 20 Multivariate vs. Bivariate Approach . . . . . . . .