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Beta autoregressive moving average models

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Cited by:

  1. Víctor Leiva & Helton Saulo & Rubens Souza & Robert G. Aykroyd & Roberto Vila, 2021. "A new BISARMA time series model for forecasting mortality using weather and particulate matter data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 346-364, March.
  2. Guilherme Pumi & Taiane Schaedler Prass & Rafael Rigão Souza, 2021. "A dynamic model for double‐bounded time series with chaotic‐driven conditional averages," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 68-86, March.
  3. Palm, Bruna G. & Bayer, Fábio M. & Cintra, Renato J., 2022. "2-D Rayleigh autoregressive moving average model for SAR image modeling," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
  4. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
  5. Andréa V. Rocha & Francisco Cribari-Neto, 2017. "Erratum to: Beta autoregressive moving average models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 451-459, June.
  6. Phillip Li, 2018. "Efficient MCMC estimation of inflated beta regression models," Computational Statistics, Springer, vol. 33(1), pages 127-158, March.
  7. Abraão D. C. Nascimento & Maria C. S. Lima & Hassan Bakouch & Najla Qarmalah, 2023. "Scaled Muth–ARMA Process Applied to Finance Market," Mathematics, MDPI, vol. 11(8), pages 1-18, April.
  8. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
  9. Božidar Popović & Saralees Nadarajah & Miroslav Ristić, 2013. "A new non-linear AR(1) time series model having approximate beta marginals," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(1), pages 71-92, January.
  10. Frédy Pokou & Jules Sadefo Kamdem & François Benhmad, 2024. "Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1349-1399, April.
  11. Vinicius Q. S. Maior & Francisco José A. Cysneiros, 2018. "SYMARMA: a new dynamic model for temporal data on conditional symmetric distribution," Statistical Papers, Springer, vol. 59(1), pages 75-97, March.
  12. Guillermo Ferreira & Jorge Figueroa-Zúñiga & Mário Castro, 2015. "Partially linear beta regression model with autoregressive errors," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 752-775, December.
  13. Scher, Vinícius T. & Cribari-Neto, Francisco & Bayer, Fábio M., 2024. "Generalized βARMA model for double bounded time series forecasting," International Journal of Forecasting, Elsevier, vol. 40(2), pages 721-734.
  14. Zheng, Tingguo & Chen, Rong, 2017. "Dirichlet ARMA models for compositional time series," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 31-46.
  15. Billio Monica & Casarin Roberto, 2011. "Beta Autoregressive Transition Markov-Switching Models for Business Cycle Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-32, September.
  16. Cribari-Neto, Francisco & Scher, Vinícius T. & Bayer, Fábio M., 2023. "Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy," International Journal of Forecasting, Elsevier, vol. 39(1), pages 98-109.
  17. Francisco JA Cysneiros, 2018. "Symmetric Regression Model for Temporal Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(2), pages 44-45, February.
  18. Gorgi, P. & Koopman, S.J., 2023. "Beta observation-driven models with exogenous regressors: A joint analysis of realized correlation and leverage effects," Journal of Econometrics, Elsevier, vol. 237(2).
  19. Tingguo Zheng & Han Xiao & Rong Chen, 2021. "Generalized Autoregressive Moving Average Models with GARCH Errors," Papers 2105.05532, arXiv.org.
  20. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
  21. Zheng, Tingguo & Xiao, Han & Chen, Rong, 2015. "Generalized ARMA models with martingale difference errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 492-506.
  22. repec:jss:jstsof:34:i02 is not listed on IDEAS
  23. Tingguo Zheng & Han Xiao & Rong Chen, 2022. "Generalized autoregressive moving average models with GARCH errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 125-146, January.
  24. Maia, Gisele de Oliveira & Barreto-Souza, Wagner & Bastos, Fernando de Souza & Ombao, Hernando, 2021. "Semiparametric time series models driven by latent factor," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1463-1479.
  25. Willams B. F. da Silva & Pedro M. Almeida‐Junior & Abraão D. C. Nascimento, 2023. "Generalized gamma ARMA process for synthetic aperture radar amplitude and intensity data," Environmetrics, John Wiley & Sons, Ltd., vol. 34(7), November.
  26. Cepeda-Cuervo Edilberto & Garrido Liliana, 2015. "Bayesian beta regression models with joint mean and dispersion modeling," Monte Carlo Methods and Applications, De Gruyter, vol. 21(1), pages 49-58, March.
  27. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
  28. Moizes Melo & Airlane Alencar, 2020. "Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 830-857, November.
  29. Andréa Rocha & Alexandre Simas, 2011. "Influence diagnostics in a general class of beta regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 95-119, May.
  30. Cristine Rauber & Francisco Cribari-Neto & Fábio M. Bayer, 2020. "Improved testing inferences for beta regressions with parametric mean link function," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 687-717, December.
  31. Melchior, Cristiane & Zanini, Roselaine Ruviaro & Guerra, Renata Rojas & Rockenbach, Dinei A., 2021. "Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches," International Journal of Forecasting, Elsevier, vol. 37(2), pages 825-837.
  32. Denis Surzhko, 2017. "Bayesian Approach to PD Calibration and Stress-testing in Low Default Portfolios," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(2), pages 1-6.
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