Abstract
Quite often it is not possible to postulate an appropriate parametric form for the DGP under study. In such cases, semi- and nonparametric methods are called for. Certain of these methods introduced in Chapter 9 can be easily extended to the multivariate (vector) framework. Specifically, let \(Y_t\;=\;(Y_{1,t},\ldots,Y_{m,t})\prime\) denote an m-dimensional process.
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De Gooijer, J.G. (2017). Vector Semi- and Nonparametric Methods. In: Elements of Nonlinear Time Series Analysis and Forecasting. Springer Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-43252-6_12
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DOI: https://doi.org/10.1007/978-3-319-43252-6_12
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