تجزیه و تحلیل داده‌های مقادیر فرین دمای شهر تبریز

1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390. 1. Ansari Esfeh, M., Kattan, L., Lam, W.H.K., Ansari Esfe, R., Salari, M. (2020), Compound generalized extreme value distribution for modeling the effects of monthly and seasonal variation on the extreme travel delays for vulnerability analysis of road network. Transportation Research Part C: Emerging Technologies, Volume 120, pp 1-30 2. Cheng, L. AghaKouchak, A. Gilleland, E. Katz, R. W. (2014), non-stationary extreme value analysis in a changing climate. Clim. Change, 127, pp. 353-369. 3. Cooley, D. and Sain, S. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of agricultural, biological,and environmental statistics, 15(3):381–302. 4. Davison, A. C. (1983), Modeling excesses over High Thresholds, with an Application. In Statistical and 5. Applications, ed Tiago de Oliveira, NATO ASI Series, Dordresht: Reidel, pp. 361-382 6. Davison, A. C. and Gholamrezaee, M. M. (2012). Geostatistics of extremes. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, volume 368, pages 581–608. The Royal Society. 7. Davison, A.C. and Smith, R.L. (1990), Models for Exceedances over High Thresholds, J. R. Statist. Soc. B 52, No. 3, 393-332. 8. Fisher, R.A. and Tippet, L. H. C. (1928), Limiting forms of the Frequency Distribution of the Large or Smallest Member of Sample. Proc. Cambridge Phil. Soc. 24, 180-190 9. Grimshaw, S. D. (1993), Computing Maximum Likelihood Estimation for the Generalized Pareto Distribution, Technometrics, Vol. 35 No. 2, 185-191. 10. Hosking, J. (1985). Algorithm as 215: Maximum-likelihood estimation of the parameters of the generalized extreme-value distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 33(3):301–310. 11. Hosking, J.R.M. and Wallis. J.R.(1987), Parameter and Quantile Estimation for the Generalized Pareto Distribution, Technometrics, 29, 339-349. 12. Hosking, J.R.M., Wallis. J.R. and Wood, E. F. (1985), Estimation of the Generalized Extreme Value Distribution by the Method of Probability Weighted Moments. Technometrics, 27, 251-261. 13. Joe, H. (1987), Estimation of Quantiles of the Maximum of N Observations, Biometrica, 74, 347-354. 14. Kang, S.; Song, J. (2017) Parameter and quantile estimation for the generalized Pareto distribution in peaks over threshold framework. J. Korean Stat. Soc., 46, 487–501. 15. Kumar, D., Nassar, M., Malik, M.R. (2020), Estimation of the Location and Scale Parameters of Generalized Pareto Distribution Based on Progressively Type-II Censored Order Statistics. Ann. Data. Sci. https://doi.org/10.1007/s40745-020-00266-0 16. Langousis, A., Mamalakis, A., Puliga, M., Deidda, R. (2016), Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database. Water Resource. Res., 52, 2659–2681. 17. Leadbetter, M. R., Lindgren, G., and Rootzen, H. (1983), Extremes and Related Properties of Random 18. Sequences and Processes. Springer-Verlag, New York Inc. 19. Leonard, M. Metcalfe, A. Lambert, M. (2008), Frequency Analysis of Rainfall and Stream Flows Extremes According for Seasonal and Climatic Partitions. Journal of Hydrology, 348, 135-147. 20. Martins, A.L.A., Liska, G.R., Beijo, L.A. (2020), Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil. SN Appl. Sci. 2, 1479. https://doi.org/10.1007/s42452-020-03199-8 21. Nagatsuka, H., Balakrishnan, N. (2021), Efficient likelihood-based inference for the generalized Pareto distribution. Ann Inst Stat Math. https://doi.org/10.1007/s10463-020-00782-z 22. Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics, 3:119–131. 23. Rajabi, M.R., Modarres, R. (2008), Extreme Value Frequency Analysis of Wind Data for Isfahan, Iran. Journal of Wind Engineering and Industrial Aerodynamics 96, 78-87. 24. Rootzen, H. and Tajvidai, N. (1997), Extreme Value Statistics and Wind Storm Losses: A Case Study, Scandinavian Acturial Journal, 1: 70-94. 25. Schlögl, M. Laaha, G. (2017), Extreme weather exposure identification for road networks–a comparative assessment of statistical methods. Nat. Hazards Earth. Sci., 17, pp. 515-531. 26. Sharpe, M., Juárez, M. A., (2021), Estimation of the Pareto and related distributions – A reference-intrinsic approach, Communications in Statistics - Theory and Methods, DOI: 10.1080/03610926.2021.1916826 27. Smith, R. L. (1984), Threshold Method for Sample Extremes. In Statistical Extremes and Applications, 28. ed, T. Tiago de Oliveira, Dordrecht: Reidal, 261-638. 29. Smith, R. L. (1985), Maximum Likelihood Estimation in a class of Nonregular Cases. Biometrica, 72, 67-90 30. Smith, R. L. (1987), Estimating Tails of Probability Distributions. The Annals of Statistics, 15, 1173-1207. 31. Wenuri, H. Xu, S. Naji, S. (2008), Evaluation of GEV Model for Frequency Analysis of Annual Maximum Water Levels in the Coast of United States. Ocean Engineering. 35, 1132-1147. 32. Yi, H., Liang P., Dabao, Zh., Zifeng, Zh., (2021), Risk Analysis via Generalized Pareto Distributions. Journal of Business & Economic Statistics, DOI: 10.1080/07350015.2021.1874390.