Koopman, Siem Jan creator Shephard, Neil arg spa image/jpeg xvii, 370 p. 24 cm. 1. Introduction, Siem Jan Koopman and Neil Shephard - 2. The Development of a Time Series Methodology: from Recursive Residuals to Dynamic Conditional Score Models, Andrew Harvey - 3. A State-Dependent Model for Inflation Forecasting, Andrea Stella and James H. Stock - 4. Measuring the Tracking Error of Exchange Traded Funds, Giuliano De Rossi - 5. Measuring the Dynamics of Global Business Cycle Connectedness, Francis X. Diebold and Kamil Yilmaz - 6. Inferring and Predicting Global Temperature Trends, Craig Ansley and Piet de Jong - 7. Forecasting the Boat Race, Geert Mesters and Siem Jan Koopman - 8. Tests for Serial Dependence in Static, Non-Gaussian Factor Models, Gabriele Fiorentini and Enrique Sentana - 9. Inference for Models with Asymmetric α-Stable Noise Processes, Tatjana Lemke and Simon J. Godsill - 10. Martingale Unobserved Component Models, Neil Shephard - 11. More is Not Always Better: Kalman Filtering in Dynamic Factor Models, Pilar Poncela and Esther Ruiz - 12. On Detecting End-of-Sample Instabilities, Fabio Busetti - 13. Improved Frequentist Prediction Intervals for Autoregressive Models by Simulation, Jouni Helske and Jukka Nyblom - 14. The Superiority of the LM Test in a Class of Econometric Models Where the Wald Test Performs Poorly, Jun Ma and Charles R. Nelson - 15. Generalised Linear Spectral Models, Tommaso Proietti and Alessandra Luati 330.43 Econometría 978-0-19-968366-6 https://biblioeco.unsa.edu.ar/pmb/images/libros/L126251.jpg https://biblioeco.unsa.edu.ar/pmb/images/libros/L126251.jpg AR-UNSa-BCEJYS 260407 20260407155703.0 40734 spa