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Robust streamflow forecasting: a Student's t-mixture vector autoregressive model
(SPRINGER, 2022)
Accurate streamflow forecasting is one of the main challenges in the management of reservoirs, where autoregressive models have been commonly used. Typically, the noise of these models is considered Gaussian. However, this ...
Measuring time series predictability using support vector regression
(TAYLOR & FRANCIS INC, 2008)
Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive ...
Autoregressive vectors and the identification of monetary policy shocks in ArgentinaVectores autoregresivos e identificación de shocks de política monetaria en Argentina
(Instituto de Economía y Finanzas. Facultad de Ciencias Económicas. Universidada Nacional de Córdoba., 2004)
Autoregressive vectors model in the analysis of the determinants of soybean production in Brazil
(Universidade Federal de Santa Maria, 2020)
Multivariate Threshold Models: TVARs and TVECMsMultivariate Threshold Models: TVARs and TVECMs
(Sociedade Brasileira de Econometria, 2003)
Does curvature enhance forecasting?
(Banco Central do Brasil, 2008)
In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential three-factor Diebold and Li (2006) model is proposed, where a fourth factor ...