Time series regression models for zero-inflated proportions

References

• Johnson N L, Kotz S, Balakrishnan N. Continuous univariate distributions. Vol. 2. New York: John Wiley and Sons; 1995.
   Google Scholar
• Ferrari S, Cribari-Neto F. Beta regression for modelling rates and proportions. J Appl Stat. 2004;31(7):799–815. doi: 10.1080/0266476042000214501
   Web of Science ®Google Scholar
• Rocha AV, Cribari-Neto F. Beta autoregressive moving average models. Test. 2009;18(3):529–545. doi: 10.1007/s11749-008-0112-z
   Web of Science ®Google Scholar
• da-Silva CQ, Migon HS, Correia LT. Dynamic Bayesian beta models. Comput Stat Data Anal. 2011;55:2074–2089. doi: 10.1016/j.csda.2010.12.011
   Web of Science ®Google Scholar
• Guolo A, Varin C. Beta regression for time series analysis of bounded data, with application to Canada Google® flu trends. Ann Appl Stat. 2014;8(1):74–88. doi: 10.1214/13-AOAS684
   Web of Science ®Google Scholar
• Ospina R, Ferrari SL. A general class of zero-or-one inflated beta regression models. Comput Stat Data Anal. 2012;56(6):1609–1623. doi: 10.1016/j.csda.2011.10.005
   Web of Science ®Google Scholar
• Carrasco JMF, Reid N. Simplex regression models with measurement error. Commun Stat Simul Comput. 2021;50(11):3420–3435. doi: 10.1080/03610918.2019.1626881
   Web of Science ®Google Scholar
• Liu P, Yuen KC, Wu LC, et al. Zero-one-inflated simplex regression models for the analysis of continuous proportion data. Stat Interface. 2020;13(2):193–208. doi: 10.4310/SII.2020.v13.n2.a5
   Web of Science ®Google Scholar
• Yang M, Zamba GK, Cavanaugh JE. Markov regression models for count time series with excess zeros: a partial likelihood approach. Stat Methodol. 2013;14:26–38. doi: 10.1016/j.stamet.2013.02.001
   Web of Science ®Google Scholar
• Sathish V, Mukhopadhyay S, Tiwari R. Autoregressive and moving average models for zero? Inflated count time series. Stat Neerl. 2022;76(2):190–218. doi: 10.1111/stan.12255
   Web of Science ®Google Scholar
• Balakrishna N, Anvar PM, Abraham B. Zero-modified count time series with Markovian intensities. J Stat Plan Inference. 2024;229:Article ID 106092. doi: 10.1016/j.jspi.2023.07.006
   PubMed Web of Science ®Google Scholar
• Fokianos K, Kedem B. Partial likelihood inference for time series following generalized linear models. J Time Ser Anal. 2004;25(2):173–197. doi: 10.1046/j.0143-9782.2003.00344.x
   Web of Science ®Google Scholar
• Dunn PK, Smyth GK. Randomized quantile residuals. J Comput Graph Stat. 1996;5(3):236–244.
   Google Scholar
• Kedem B, Fokianos K. Regression models for time series analysis; 2002.
   Google Scholar
• Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics. 1992;34(1):1–14. doi: 10.2307/1269547
   Web of Science ®Google Scholar
• Fokianos K, Rahbek A, Tjøstheim D. Poisson autoregression. J Amer Statist Assoc. 2009; 104(488):1430–1439. doi: 10.1198/jasa.2009.tm08270
   Web of Science ®Google Scholar
• Jensen ST, Rahbek A. On the law of large numbers for (geometrically) ergodic Markov chains. Econ Theory. 2007;23(4):761–766. doi: 10.1017/S0266466607070326
   Google Scholar
• Stasinopoulos DM, Rigby RA. Generalized additive models for location scale and shape (GAMLSS) in R. J Stat Softw. 2008;23(7):1–46.
   Web of Science ®Google Scholar
• Akaike H. A new look at the statistical model identifications. IEEE Trans Automat Contr. 1974;19:716–723. doi: 10.1109/TAC.1974.1100705
   Google Scholar
• Schwarz G. Estimating the dimension of a model. Ann Stat. 1978;6(2):461–464. doi: 10.1214/aos/1176344136
   Web of Science ®Google Scholar
• Contosta AR, Casson NJ, Garlick S, et al. Northern forest winters have lost cold, snowy conditions that are important for ecosystems and human communities. Ecol Appl. 2019;29(7):Article ID e01974. doi: 10.1002/eap.v29.7
   PubMed Web of Science ®Google Scholar
• Bartoń K. MuMIn: multi-model inference in R; 2022.
   Google Scholar
• Bayer FM, Bayer DM, Pumi G. Kumaraswamy autoregressive moving average models for double bounded environmental data. J Hydrol (Amst). 2017;555:385–396. doi: 10.1016/j.jhydrol.2017.10.006
   Web of Science ®Google Scholar
• Lu J, Meyer S. An endemic–epidemic beta model for time series of infectious disease proportions. J Appl Stat. 2022;49(15):3769–3783. doi: 10.1080/02664763.2021.1962264
   PubMed Web of Science ®Google Scholar