Browse Journals

[1] M. S. Al-Qassam and J. A. Lane, Forecasting exponential autoregressive models of order 1, Journal of Time Series Analysis 10(2) (1989), 95-113.

DOI: https://doi.org/10.1111/j.1467-9892.1989.tb00018.x

[2] J. Allal and S. El Melhaoui, Optimal detection of exponential component in autoregressive models, Journal of Time Series Analysis 27(6) (2006), 793-810.

DOI: https://doi.org/10.1111/j.1467-9892.2006.00489.x

[3] E. Amiri, Forecasting GDP growth rate with nonlinear models, 1st International Conference on Econometrics Methods and Applications, ICEKU2012, August 25-27. Sanandaj, Iran (2012), 1-18.

[4] A. Amondela and C. Francq, Concepts and tools for nonlinear time-series modelling, In Handbook of Computational Econometrics (Editors D. A. Belsley and E. J. Kontoghiorghes), John Wiley & Sons, Ltd., Chichester, U. K. (2009), 377-427.

[5] R. Baragona, F. Battaglia and D. Cucina, A note on estimating autoregressive exponential models, Quaderni di Statistica 4 (2002), 71-88.

[6] I. V. Basawa and R. Lund, Large sample properties of parameters estimates for periodic ARMA models, Journal of Time Series Analysis 22(6) (2001), 651-663.

DOI: https://doi.org/10.1111/1467-9892.00246

[7] A. Bibi and A. Gautier, Stationarity and asymptotic inference of some periodic bilinear models, Comptes Rendus Mathematique 341(11) (2005), 679-682.

DOI: https://doi.org/10.1016/j.crma.2005.09.040

[8] T. Bollerslev and E. Ghysels, Periodic autoregressive conditional heteroscedasticity, Journal of Business and Economic Statistics 14(2) (1996), 139-152.

[9] P. J. Brockwell and R. A. Davis, Time Series: Theory and Methods, Springer-Verlag, New York, 1991.

[10] K. S. Chan and H. Tong, On the use of the deterministic Lyapunov function for the ergodicity of stochastic difference equations, Advances in Applied Probability 17(3) (1985), 666-678.

DOI: https://doi.org/10.2307/1427125

[11] J. G. De Gooijer, Elements of Nonlinear Time Series Analysis and Forecasting, Springer International Publishing, 2017.

[12] H. Ghosh, B. Gurung and P. Gupta, fitting EXPAR models through the extended Kalman filter, Sankhya: The Indian Journal of Statistics 77(1) (2015), 27-44.

DOI: https://doi.org/10.1007/s13571-014-0085-8

[13] E. G. Gladyshev, Periodically correlated random sequences, Soviet Mathematics Doklady 2 (1961), 385-388.

[14] B. Gurung, An application of exponential autoregressive (EXPAR) nonlinear time-series model, International Journal of Information and Computation Technology 3(4) (2013), 261-266.

[15] V. Haggan and T. Ozaki, Modeling nonlinear random vibrations using an amplitude-dependent autoregressive time series model, Biometrika 68(1) (1981), 189-196.

DOI: https://doi.org/10.1093/biomet/68.1.189

[16] I. A. Ibragimov, A central limit theorem for a class of dependent random variables, Theory of Probability & Its Applications 8(1) (1963), 83-89.

DOI: https://doi.org/10.1137/1108007

[17] K. Ishizuka, H. Kato and T. Nakatani, Speech Signal Analysis with Exponential Autoregressive Model, Proc. the 30th International Conference of Acoustics, Speech and Signal Processing, Institute of Electrical and Electronics Engineers Inc., Philadelphia, PA, United States 1 (2005), 225-228.

[18] P. Katsiampa, A new approach to modelling nonlinear time series: Introducing the ExpAR-ARCH and ExpAR-GARCH models and applications, 4th Student Conference on Operational Research, Germany (2014), 34-51.

DOI: https://doi.org/10.4230/OASIcs.SCOR.2014.34

[19] H. L. Koul and A. Schick, Efficient estimation in nonlinear autoregressive time series models, Bernoulli 3(3) (1997), 247-277.

DOI: https://doi.org/10.2307/3318592

[20] P. A. W. Lewis and B. K. Ray, Nonlinear modelling of periodic threshold autoregressions using TSMARS, Journal of Time Series Analysis 23(4) (2002), 459-471.

DOI: https://doi.org/10.1111/1467-9892.00269

[21] A. I. McLeod, Diagnostic checking periodic auto regression models with application, Journal of Time Series Analysis 15(2) (1994), 221-233.

DOI: https://doi.org/10.1111/j.1467-9892.1994.tb00186.x

[22] M. Merzougui, Estimation in periodic restricted EXPAR(1) models, Communications in Statistics-Simulation and Computation 47(10) (2018), 2819-2828.

DOI: https://doi.org/10.1080/03610918.2017.1361975

[23] M. Merzougui, H. Dridi and A. Chadli, Test for periodicity in restrictive EXPAR models, Communications in Statistics - Theory and Methods 45(9) (2016), 2770-2783.

DOI: https://doi.org/10.1080/03610926.2014.887110

[24] A. Messaoud, C. Weihs and F. Hering, Nonlinear Time Series Modelling: Monitoring a Drilling Process, In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger and W. Gaul (Editors), From Data and Information Analysis to Knowledge Engineering, pages 302-309, Springer, Heidelberg, 2006.

[25] T. Ozaki, Non-linear time series models for non-linear random vibrations, Journal of Applied Probability 17(1) (1980), 84.93.

DOI: https://doi.org/10.2307/3212926

[26] T. Ozaki, The statistical analysis of perturbed limit cycle processes using nonlinear time series models, Journal of Time Series Analysis 3(1) (1982), 29-41.

DOI: https://doi.org/10.1111/j.1467-9892.1982.tb00328.x

[27] T. Ozaki, 2 Non linear time series models and dynamical system, Handbook of Statistics 5 (1985), 25-83.

DOI: https://doi.org/10.1016/S0169-7161(85)05004-0

[28] M. B. Priestley, Non-Linear and Non-Stationary Time Series Analysis, Academic Press, New York, 1988.

[29] Q. Shao, Mixture periodic autoregressive time series models, Statistics & Probability Letters 76(6) (2006), 609-618.

DOI: https://doi.org/10.1016/j.spl.2005.09.015

[30] Z. Shi and H. Aoyama, Estimation of the exponential autoregressive time series model by using genetic algorithm, Journal of Sound and Vibration 205(3) (1997), 309-321.

DOI: https://doi.org/10.1006/jsvi.1997.1048

[31] Z. Shi, Y. Tamura and T. Ozaki, Monitoring the stability of BWR oscillation by nonlinear time series modeling, Annals of Nuclear Energy 28(10) (2001), 953-966.

DOI: https://doi.org/10.1016/S0306-4549(00)00099-2

[32] N. Terui and H. K. Van Dijk, Combined forecasts from linear and nonlinear time series models, Tinbergen Institute Discussion Paper Series. Econometric Institute Report EI-9949/A, 1999.

[33] Y. G. Tesfaye, M. M. Meerschaert and P. L. Anderson, Identification of PARMA models and their application to the modeling of river flows, Water Resources Research 42(1) (2006), W01419.

DOI: https://doi.org/10.1029/2004WR003772

[34] D. Tjøstheim, Estimation in nonlinear time series models, Elsevier Science Publishers B.V. North-Holland, Stochastic Processes and their Applications 21(2) (1986), 251-273.

DOI: https://doi.org/10.1016/0304-4149(86)90099-2

[35] H. Tong, Non-Linear Time Series: A Dynamical System Approach, Oxford University Press, Oxford, 1990.

[36] A. V. Vecchia and R. Ballerini, Testing for periodic autocorrelations in seasonal time series data, Biometrika 78(1) (1991), 53.63.

DOI: https://doi.org/10.1093/biomet/78.1.53