Monday, April 23, 2018 - 1:00pm - 1:30pm
Ines Wilms (Katholieke Universiteit Leuven)
The Vector AutoRegressive Moving Average (VARMA) model is fundamental
to the study of multivariate time series. However, estimation becomes challenging in
even relatively low-dimensional VARMA models. With growing interest in the simultaneous
modeling of large numbers of marginal time series, many authors have abandoned
the VARMA model in favor of the Vector AutoRegressive (VAR) model, which is seen as a
simpler alternative, both in theory and practice, in this high-dimensional context. However,
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