Cited By
View all- Jamil WBouchachia A(2018)Model Selection in Online Learning for Times Series ForecastingAdvances in Computational Intelligence Systems10.1007/978-3-319-97982-3_7(83-95)Online publication date: 11-Aug-2018
Linear autoregressive models serve as basic representations of discrete time stochastic processes. Different attempts have been made to provide non-linear versions of the basic autoregressive process, including different versions based on kernel ...
Varying-coefficient models have attracted great attention in nonlinear time series analysis recently. In this paper, we consider a semi-parametric functional-coefficient autoregressive model, called the radial basis function network-based state-dependent ...
The least-squares method for estimating the parameters of the vector autoregressive (VAR) model is considered and new estimates for the covariance matrix of the VAR model input noise and the prediction error covariance matrix are derived. Based on these ...
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