- Andersen, T., Bollerslev, T. and Diebold, F.: 2006, Parametric and nonparametric measurement of volatility, in G. Elliott, C. Granger and A. Timmermann (eds), Handbook of Financial Econometrics, NorthHolland, Amsterdam.
Paper not yet in RePEc: Add citation now
ardle, W., L utkepohl, H. and Chen, R.: 1997, A review of nonparametric time series analysis, International Statistical Review 65, 49–72.
- ardle, W.: 1990, Applied Nonparametric Regression, Cambridge University Press, Cambridge. H
Paper not yet in RePEc: Add citation now
Bollerslev, T.: 1986, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 21, 307–328.
- Carvalho, A. and Skoulakis, G.: 2004, Ergodicity and existence of moments for local mixture of linear autoregressions, Technical report, Northwestern University.
Paper not yet in RePEc: Add citation now
- Carvalho, A. and Tanner, M.: 2005a, Mixture-of-experts of autoregressive time series: asymptotic normality and model specification, IEEE Transactions on Neural Networks 16, 39–56.
Paper not yet in RePEc: Add citation now
- Carvalho, A. and Tanner, M.: 2005b, Modeling nonlinear time series with mixture-of-experts of generalized linear models, The Canadian Journal of Statistics 33, 1–17.
Paper not yet in RePEc: Add citation now
Chan, K. S. and Tong, H.: 1986, On estimating thresholds in autoregressive models, Journal of Time Series Analysis 7, 179–190.
Chen, X. and Shen, X.: 1998, Sieve Extremum Estimates for Weakly Dependent Data, Econometrica 66, 289– 314.
- Chen, X. and White, H.: 1998, Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators, IEEE Transactions on Information Theory 18, 17–39.
Paper not yet in RePEc: Add citation now
Christoffersen, P. F.: 1998, Evaluating interval forecasts, International Economic Review 39, 841–862.
da Rosa, J. C., Veiga, A. and Medeiros, M. C.: 2008, Tree-structured smooth transition regression models, Computational Statistics and Data Analysis 52, 2469–2488.
- Dempster, A. P., Laird, N. M. and Rubin, D. B.: 1977, Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B 39, 1–38.
Paper not yet in RePEc: Add citation now
ESTIMATION AND ASYMPTOTIC THEORY FOR A NEW CLASS OF MIXTURE MODELS 31 McAleer, M.: 2005, Automated inference and learning in modeling financial volatility, Econometric Theory 21, 232–261.
- Fan, J. and Yao, Q.: 2003, Nonlinear Time Series: Nonparametric and Parametric Methods, Springer-Verlag, New York, NY.
Paper not yet in RePEc: Add citation now
- Gallant, A. R. and White, H.: 1992, On learning the derivatives of an unknown mapping with multilayer feedforward networks, Neural Networks 5, 129–138.
Paper not yet in RePEc: Add citation now
- Granger, C. W. J. and Ter asvirta, T.: 1993, Modelling Nonlinear Economic Relationships, Oxford University Press, Oxford.
Paper not yet in RePEc: Add citation now
- Hornik, K., Stinchombe, M. and White, H.: 1990, Universal approximation of an unknown mapping and its derivatives using multi-layer feedforward networks, Neural Networks 3, 551–560. H
Paper not yet in RePEc: Add citation now
- Huerta, G., Jiang, W. and Tanner, M.: 2001, Mixtures of time series models, Journal of Computational and Graphical Statistics 10, 82–89.
Paper not yet in RePEc: Add citation now
- Huerta, G., Jiang, W. and Tanner, M.: 2003, Time series modeling via hierachical mixtures, Statistica Sinica 13, 1097–1118.
Paper not yet in RePEc: Add citation now
- Jacobs, R. A., Jordan, M. I., Nowlan, S. J. and Hinton, G. E.: 1991, Adaptive mixtures of local experts, Neural Computation 3, 79–87.
Paper not yet in RePEc: Add citation now
- Jiang, W. and Tanner, M.: 1999, On the identifiability of mixtures-of-experts, Neural Networks 12, 1253– 1258.
Paper not yet in RePEc: Add citation now
- Jordan, M. I. and Jacobs, R. A.: 1994, Hierarchical mixtures of experts and the EM algorithm, Neural Computation 6, 181–214.
Paper not yet in RePEc: Add citation now
- Kuan, C. M. and White, H.: 1994, Artificial neural networks: An econometric perspective, Econometric Reviews 13, 1–91.
Paper not yet in RePEc: Add citation now
- Le, N., Martin, R. and Raftery, A.: 1996, Modeling flat streches, bursts, and outliers in time series using mixture transition distribution models, Journal of the American Statistical Association 91, 1504–1515.
Paper not yet in RePEc: Add citation now
- Luukkonen, R., Saikkonen, P. and Ter asvirta, T.: 1988, Testing linearity against smooth transition autoregressive models, Biometrika 75, 491–499.
Paper not yet in RePEc: Add citation now
- MacKay, D. J. C.: 1992, Bayesian interpolation, Neural Computation 4, 415–447.
Paper not yet in RePEc: Add citation now
Medeiros, M. and Veiga, A.: 2005, Flexible coeficient smooth transition time series model, IEEE Transactions on Neural Networks 16, 97–113.
Medeiros, M., Ter asvirta, T. and Rech, G.: 2006, Building neural network models for time series: A statistical approach, Journal of Forecasting 25, 49–75.
- Nowlan, S. J.: 1990, Maximum likelihood competitive learning, Advances in Neural Information Processing Systems, Vol. 2, Morgan Kaufmann, pp. 574–582.
Paper not yet in RePEc: Add citation now
Poon, S. and Granger, C.: 2003, Forecasting volatility in financial markets, Journal of Economic Literature 41, 478–539.
- Quinn, B., McLachlan, G. and Hjort, L.: 1987, A note on the Aitkin-Rubin approach to hypothesis testing in mixture models, Journal of the Royal Statistal Society, Series B 49, 311–314.
Paper not yet in RePEc: Add citation now
Rech, G., Ter asvirta, T. and Tschernig, R.: 2001, A simple variable selection technique for nonlinear models, Communications in Statistics, Theory and Methods 30, 1227–1241.
- Taylor, S.: 1986, Modelling Financial Time Series, Wiley, Chichester.
Paper not yet in RePEc: Add citation now
- Ter asvirta, T.: 1994, Specification, estimation, and evaluation of smooth transition autoregressive models, Journal of the American Statistical Association 89, 208–218.
Paper not yet in RePEc: Add citation now
- Tong, H. and Lim, K.: 1980, Threshold autoregression, limit cycles and cyclical data (with discussion), Journal of the Royal Statistical Society, Series B 42, 245–292.
Paper not yet in RePEc: Add citation now
- Tong, H.: 1978, On a threshold model, in C. H. Chen (ed.), Pattern Recognition and Signal Processing, Sijthoff and Noordhoff, Amsterdam.
Paper not yet in RePEc: Add citation now
- Tong, H.: 1990, Non-linear Time Series: A Dynamical Systems Approach, Vol. 6 of Oxford Statistical Science Series, Oxford University Press, Oxford.
Paper not yet in RePEc: Add citation now
- Trapletti, A., Leisch, F. and Hornik, K.: 2000, Stationary and integrated autoregressive neural network processes, Neural Computation 12, 2427–2450.
Paper not yet in RePEc: Add citation now
van Dijk, D., Ter asvirta, T. and Franses, P. H.: 2002, Smooth transition autoregressive models - a survey of recent developments, Econometric Reviews 21, 1–47.
- Weigend, A. S., Mangeas, M. and Srivastava, A. N.: 1995, Nonlinear gated experts for time series: Discovering regimes and avoiding overfitting, International Journal of Neural Systems 6, 373–399.
Paper not yet in RePEc: Add citation now
- Wood, S., Jiang, W. and Tanner, M.: 2001, Bayesian mixture of splines for spatially adaptative nonparametric regression, Biometrika 89, 513–528.
Paper not yet in RePEc: Add citation now
- Zeevi, A., Meir, R. and Adler, R.: 1998, Non-linear models for time series using mixtures of autoregressive models, Technical report, Technion. Departamento de Economia PUC-Rio PontifÃcia Universidade Católica do Rio de Janeiro Rua Marques de Sâo Vicente 225 - Rio de Janeiro 22453-900, RJ Tel.(21) 35271078 Fax (21) 35271084 www.econ.puc-rio.br flavia@econ.puc-rio.br
Paper not yet in RePEc: Add citation now