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Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes

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  • Dahlhaus, R.
  • Neumann, M.
  • Von Sachs, R.

Abstract

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  • Dahlhaus, R. & Neumann, M. & Von Sachs, R., 1997. "Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes," SFB 373 Discussion Papers 1997,34, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:199734
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    Cited by:

    1. Yang Li & Wei-Gang Cui & Mei-Lin Luo & Ke Li & Lina Wang, 2017. "High-resolution time–frequency representation of EEG data using multi-scale wavelets," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(12), pages 2658-2668, September.
    2. Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin, 2017. "Quantile spectral analysis for locally stationary time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1619-1643, November.
    3. Offer Lieberman & Peter C. B. Phillips, 2014. "Norming Rates And Limit Theory For Some Time-Varying Coefficient Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 592-623, November.
    4. Panayiotis Tzeremes, 2020. "The impact of total factor productivity on energy consumption and CO2 emissions in G20 countries," Economics Bulletin, AccessEcon, vol. 40(3), pages 2179-2192.
    5. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    6. Hoffmann, Marc, 1999. "On nonparametric estimation in nonlinear AR(1)-models," Statistics & Probability Letters, Elsevier, vol. 44(1), pages 29-45, August.
    7. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Kristensen, Dennis, 2009. "Uniform Convergence Rates Of Kernel Estimators With Heterogeneous Dependent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1433-1445, October.
    9. Piotr Fryzlewicz & Sébastien Bellegem & Rainer Sachs, 2003. "Forecasting non-stationary time series by wavelet process modelling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(4), pages 737-764, December.
    10. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    11. Dahlhaus, Rainer & Neumann, Michael H., 2001. "Locally adaptive fitting of semiparametric models to nonstationary time series," Stochastic Processes and their Applications, Elsevier, vol. 91(2), pages 277-308, February.
    12. G. E. Salcedo & R. F. Porto & S. Y. Roa & F. R. Momo, 2012. "A wavelet-based time-varying autoregressive model for non-stationary and irregular time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2313-2325, June.
    13. Battaglia, Francesco, 2005. "Outliers in functional autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 323-332, May.
    14. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    15. Shahbaz, Muhammad & Mahalik, Mantu Kumar & Shah, Syed Hasanat & Sato, João Ricardo, 2016. "Time-varying analysis of CO2 emissions, energy consumption, and economic growth nexus: Statistical experience in next 11 countries," Energy Policy, Elsevier, vol. 98(C), pages 33-48.
    16. Sato, Joao R. & Morettin, Pedro A. & Arantes, Paula R. & Amaro Jr., Edson, 2007. "Wavelet based time-varying vector autoregressive modelling," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5847-5866, August.
    17. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sato, João Ricardo, 2015. "On the relationships between CO2 emissions, energy consumption and income: The importance of time variation," Energy Economics, Elsevier, vol. 49(C), pages 629-638.
    18. Stephanos Papadamou & Nikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2019. "Spillover Effects of US QE and QE Tapering on African and Middle Eastern Stock Indices," JRFM, MDPI, vol. 12(2), pages 1-20, April.
    19. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    20. Chang Chiann & Pedro Morettin, 1999. "Estimation of Time Varying Linear Systems," Statistical Inference for Stochastic Processes, Springer, vol. 2(3), pages 253-285, October.

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