85
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Asymmetric exponential power Bayesian median autoregression with applications

&
Pages 2063-2086 | Received 30 Mar 2023, Accepted 31 Jan 2024, Published online: 08 Feb 2024

References

  • Koenker R, Bassett G. Regression quantiles. Econometrica. 1978;46:33–50. doi: 10.2307/1913643
  • Koenker R, Xiao Z. Quantile autoregression. J Am Stat Assoc. 2006;101:980–990. doi: 10.1198/016214506000000672
  • Yu K, Moyeed RA. Bayesian quantile regression. Stat Probab Lett. 2001;54:437–447. doi: 10.1016/S0167-7152(01)00124-9
  • Liu X, Luger R. Markov-switching quantile autoregression: a Gibbs sampling approach. Stud Nonlinear Dyn Econ. 2018;22:Article ID 20160078. doi: 10.1515/snde-2016-0078
  • Zeng Z, Li M. Bayesian median autoregression for robust time series forecasting. Int J Forecast. 2021;37:1000–1010. doi: 10.1016/j.ijforecast.2020.11.002
  • Zhu D, Zinde-Walsh V. Properties and estimation of asymmetric exponential power distribution. J Econom. 2009;148:86–99. doi: 10.1016/j.jeconom.2008.09.038
  • Naranjo L, Pérez CJ, Martín J. Bayesian analysis of some models that use the asymmetric exponential power distribution. Stat Comput. 2015;25:497–514. doi: 10.1007/s11222-014-9449-1
  • Nardi Y, Rinaldo A. Autoregressive process modeling via the Lasso procedure. J Multivar Anal. 2011;102:528–549. doi: 10.1016/j.jmva.2010.10.012
  • Zou H. The adaptive Lasso and its oracle properties. J Am Stat Assoc. 2006;101:1418–1429. doi: 10.1198/016214506000000735
  • Van Erp S, Oberski DL, Mulder J. Shrinkage priors for Bayesian penalized regression. J Math Psychol. 2019;89:31–50. doi: 10.1016/j.jmp.2018.12.004
  • Huber F, Koop G, Onorante L. Inducing sparsity and shrinkage in time-varying parameter models. J Bus Econ Stat. 2021;39:669–683. doi: 10.1080/07350015.2020.1713796
  • Park T, Casella G. The Bayesian Lasso. J Am Stat Assoc. 2008;103:681–686. doi: 10.1198/016214508000000337
  • Rubio FJ. Letter to the editor: on the use of improper priors for the shape parameters of asymmetric exponential power models. Stat Comput. 2015;25:1281–1287. doi: 10.1007/s11222-014-9479-8
  • Bernardi M, Bottone M, Petrella L. Bayesian quantile regression using the skew exponential power distribution. Comput Stat Data Anal. 2018;126:92–111. doi: 10.1016/j.csda.2018.04.008
  • Spiegelhalter DJ, Best NG, Carlin BP, et al. Bayesian measures of model complexity and fit. J R Stat Soc Series B. 2002;64:583–639. doi: 10.1111/1467-9868.00353
  • Maity AK, Basu S, Ghosh S. Bayesian criterion-based variable selection. J R Stat Soc Ser C. 2021;70:835–857. doi: 10.1111/rssc.12488
  • Watanabe S. Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory. J Mach Learn Res. 2010;11:3571–3594.
  • Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput. 2017;27:1413–1432. doi: 10.1007/s11222-016-9696-4
  • Yao Y, Vehtari A, Simpson D, et al. Using stacking to average Bayesian predictive distributions (with discussions). Bayesian Anal. 2018;13:917–1007. doi: 10.1214/17-BA1091
  • Bottone M, Petrella L, Bernardi M. Unified Bayesian conditional autoregression risk measures using the skew exponential power distribution. Stat Methods Appt. 2021;30:1079–1107. doi: 10.1007/s10260-020-00550-6
  • Gelman A, Hwang J, Vehtari A. Understanding predictive information criteria for Bayesian models. Stat Comput. 2014;24:997–1016. doi: 10.1007/s11222-013-9416-2
  • Burnham K, Anderson D. Model selection and multimodel inference. 2nd ed. New York: Springer; 2004.
  • Yan Y, Kottas A. A new family of error distributions for Bayesian quantile regression; 2017. arXiv, https://arxiv.org/abs/1701.05666.
  • Arellano-Valle RB, Castro LM, Genton MG, et al. Bayesian inference for shape mixtures of skewed distributions, with application to regression analysis. Bayesian Anal. 2008;3:513–540. doi: 10.1214/08-BA320
  • Pitt MK, dos Santos Silva R, Giordani P, et al. On some properties of Markov chain Monte Carlo simulation methods based on the particle filter. J Econom. 2012;171:134–151. doi: 10.1016/j.jeconom.2012.06.004

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.