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Research Article

Generalized fiducial inference for the GEV change-point model

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Received 29 Oct 2023, Accepted 28 Jul 2024, Published online: 04 Aug 2024

References

  • Adams, R.P., and MacKay, D.J (2007), ‘Bayesian Online Changepoint Detection’, preprint arXiv:0710.3742.
  • Alawadhi, F.A., and Alhulail, D. (2016), ‘Bayesian Change Points Analysis for Earthquakes Body Wave Magnitude’, Journal of Applied Statistics, 43(9), 1567–1582.
  • Ban, N., Rajczak, J., Schmidli, J., and Schär, C. (2020), ‘Analysis of Alpine Precipitation Extremes Using Generalized Extreme Value Theory in Convection – Resolving Climate Simulations’, Climate Dynamics, 55(1–2), 61–75.
  • Barry, D., and Hartigan, J.A. (1992), ‘Product Partition Models for Change Point Problems’, The Annals of Statistics, 20(1), 260–279.
  • Cai, X., Siman, F., and Liang, Y. (2024), ‘Generalized Fiducial Inference for the Lower Confidence Limit of Reliability Based on Weibull Distribution’, Communications in Statistics-Simulation and Computation, 53(5), 2097–2107.
  • Chai, J., Lu, Q., Hu, Y., Wang, S., Lai, K.K., and Liu, H. (2018), ‘Analysis and Bayes Statistical Probability Inference of Crude Oil Price Change Point’, Technological Forecasting and Social Change, 126, 271–283.
  • Chen, H., and Zhao, T. (2020), ‘Modeling Power Loss During Blackouts in China Using Non-Stationary Generalized Extreme Value Distribution’, Energy, 195, 117044.
  • Farooq, M., Shafique, M., and Khattak, M.S. (2018), ‘Flood Frequency Analysis of River Swat Using Log Pearson Type 3, Generalized Extreme Value, Normal, and Gumbel Max Distribution Methods’, Arabian Journal of Geosciences, 11, 1–10.
  • Fearnhead, P. (2006), ‘Exact and Efficient Bayesian Inference for Multiple Changepoint Problems’, Statistics and Computing, 16, 203–213.
  • Gregorio, A.D., and Iacus, S.M. (2008), ‘Least Squares Volatility Change Point Estimation for Partially Observed Diffusion Processes’, Communications in Statistics – Theory and Methods, 37(15), 2342–2357.
  • Gürler, Ü., and Yenigün, C.D. (2011), ‘Full and Conditional Likelihood Approaches for Hazard Change-Point Estimation with Truncated And Censored Data’, Computational Statistics and Data Analysis, 55(10), 2856–2870.
  • Hall, C.B., Lipton, R.B., Sliwinski, M., and Stewart, W.F. (2000), ‘A Change Point Model for Estimating the Onset of Cognitive Decline in Preclinical Alzheimer's Disease’, Statistics in Medicine, 19(11–12), 1555–1566.
  • Hannig, J. (2013), ‘Generalized Fiducial Inference Via Discretization’, Statistica Sinica, 23, 489–514.
  • Hannig, J., Iyer, H., Lai, R.C., and Lee, T.C. (2016), ‘Generalized Fiducial Inference: A Review and New Results’, Journal of the American Statistical Association, 111(515), 1346–1361.
  • Hwang, J., Lai, R.C.S., and Lee, T.C.M. (2014), ‘Computational Issues of Generalized Fiducial Inference’, Computational Statistics Data Analysis, 71, 849–858.
  • Hwang, S., Lai, R.C.S., and Lee, T.C.M. (2022), ‘Generalized Fiducial Inference for Threshold Estimation in Dose – Response and Regression Settings’, Journal of Agricultural, Biological and Environmental Statistics, 27, 109–124.
  • Liu, Y., and Hannig, J. (2017), ‘Generalized Fiducial Inference for Logistic Graded Response Models’, Psychometrika, 82, 1097–1125.
  • Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., and Zhou, B. (2021), ‘Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change’, 2.
  • Matteson, D.S., and James, N.A. (2014), ‘A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data’, Journal of the American Statistical Association, 109(505), 334–345.
  • Nam, C.F.H, Aston, J.A.D., and Johansen, A.M. (2012), ‘Quantifying the Uncertainty in Change Points’, Journal of Time Series Analysis, 33(5), 807–823.
  • Park, M.H., and Kim, J.H. (2016), ‘Estimating Extreme Tail Risk Measures with Generalized Pareto Distribution’, Computational Statistics and Data Analysis, 98, 91–104.
  • Piao, S., Zhang, X., Chen, A., Liu, Q., Lian, X., Wang, X., and Wu, X. (2019), ‘The Impacts of Climate Extremes on the Terrestrial Carbon Cycle: A Review’, Science China Earth Sciences, 62, 1551–1563.
  • Sharma, R., Das, S., and Joshi, P. (2018), ‘Score-Level Fusion Using Generalized Extreme Value Distribution and DSmT, for Multi-Biometric Systems’, IET Biometrics, 7(5), 474–481.
  • Sillmann, J., and Roeckner, E. (2008), ‘Indices for Extreme Events in Projections of Anthropogenic Climate Change’, Climatic Change, 86, 83–104.
  • Susanti, W., Adnan, A., Yendra, R., and Muhaijir, M.N. (2018), ‘The Analysis of Extreme Rainfall Events in Pekanbaru City Using Three-Parameter Generalized Extreme Value and Generalized Pareto Distribution’, Applied Mathematical Sciences, 12(2), 69–80.
  • Vostrikova, L.J. (1981), ‘Detecting “Disorder” in Multidimensional Random Processes’, Soviet Mathematics Doklady, 24, 55–59.
  • Wandler, D.V., and Hannig, J. (2012), ‘Generalized Fiducial Confidence Intervals for Extremes’, Extremes, 15, 67–87.
  • Weerahandi, S. (2012), ‘Generalized Point Estimation with Application to Small Response Estimation’, Communications in Statistics – Theory and Methods, 41(22), 4069–4095.
  • Williams, J.P., Danica M Ommen, J.P., and Hannig, J. (2023), ‘Generalized Fiducial Factor: An Alternative to the Bayes Factor for Forensic Identification of Source Problems’, The Annals of Applied Statistics, 17(1), 378–C402.
  • Yan, L., and Geng, J. (2021), ‘Generalized Fiducial Inference for the Lomax Distribution’, Journal of Statistical Computation and Simulation, 91(12), 2402–2413.
  • Yan, L., and Liu, X. (2018), ‘Generalized Fiducial Inference for Generalized Exponential Distribution’, Journal of Statistical Computation and Simulation, 88(7), 1369–1381.
  • Zhou, G.Y., Zhou, L.Y., and Shao, J.J. (2020), ‘Effects of Extreme Drought on Terrestrial Ecosystems: Review and Prospects’, Chinese Journal of Plant Ecology, 44(5), 515–525.

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