SavedAdd your journal

Journals / Bitlis Eren Üniversitesi Fen Bilimleri Dergisi / 2018 / Cilt: 7 - Sayı: 2

With Copula Method Modeling of daily maximum and minimum temperature changes in Bitlis province

Bitlis İlindeki Günlük Maksimum ve Minumum Sıcaklık Değişimlerinin Copula Metodu ile Modellenmesi

Ayşe METİN KARAKAŞ
Pages
268–275
Publication Date
2018-12-28
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that there is a strong dependence between daily maximum and minimum temperatures of Bitlis between 2012-2017 years.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper aims to examine the relationship between daily maximum and minimum temperatures of Bitlis in Turkey between 2012-2017 years with Copula method.
📊
Key Findings & Data:To present the relationship between the variables, we use copula families such as; Gumbel, Clayton, Frank, Joe, Gaussian and Survival Clayton copula.
💡
Conclusion & Impact:The results show that there is a strong dependence between daily maximum and minimum temperatures of Bitlis between 2012-2017 years.
🔬Design:Research Article
📍Scope:2012-2017 Verileri
⚙️Variables:Copula Fonksiyonları · Kendall Tau · Spearman Rho

Abstract

This paper aims to examine the relationship between daily maximum and minimum temperatures of Bitlis in Turkey between 2012-2017 years with Copula method. To present the relationship between the variables, we use copula families such as; Gumbel, Clayton, Frank, Joe, Gaussian and Survival Clayton copula. To explain dependence structures of the data set and to determine parameters of Gumbel, Clayton, Frank, Joe, Gaussian and Survival Clayton copula families, we calculate Kendall Tau and Spearman Rho values which are nonparametric. With he help of Kolmogorov Smirnov, Cramer Von Mises which are goodness of fit test, Maximum likelihood method, Akaike information Criteria ad Bayes information criteria, we find the suitable copula family for this data set. The results show that there is a strong dependence between daily maximum and minimum temperatures of Bitlis between 2012-2017 years.

Özet

Bu makalenin amacı Bitlisin 2012-2017 yılları arasındaki günlük maksimum ve minumum sıcaklıkları arasındaki ilişkiyi Copula methodu ile açıklamaktır. İlişkiyi açıklamak için çeşitli copula aileleri kullanılmıştır. Bunlar; Gumbel, Clayton, Frank, Joe, Gaussian ve Survival Claytondur. Bağımlılık yapısını açıklamak ve Gumbel, Clayton, Frank, Joe, Gaussian ve Survival Clayton copula ailelerinin parametrelerini belirlemek için parametrik olmayan metod olan Kendall Tau ve Spearman Rho değerleri hesaplanmıştır. Uyum iyiliği testleri Kolmogorov Smirnov, Cramer on Mises, maksimum oalabilirlik metodu, Akaike blgi kriteri ve Bayes bilgi kriteri yardımıyla veri seti için uygun copula ailesi bulunmuştur. Sonuçlar Bitlisin 2012 yılı ile 2017 yılları arasında günlük maksimum ve minumum sıcaklık değişimleri için güçlü bir bağımlılık olduğunu göstermiştir.

🔖

Cite This Article

KARAKAŞ, A. M. (2018). With Copula Method Modeling of daily maximum and minimum temperature changes in Bitlis province. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, Cilt: 7 - Sayı: 2, 268–275. https://ajindex.com/articles/477897

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (2)

  1. Sklar 1973. A. Random variables, joint distribution functions, and copulas. Kybernetika, 1973 9(6), 449-460.2. Genest 1986. C., & MacKay, J. The joy of copulas: Bivariate distributions with uniform marginal. The American Statistician, 40(4), 280-283.3. Genest, C., & Rivest, L. 1993. P. Statistical inference procedures for bivariate Archimedean copulas. Journal of the American Statistical Association, 88(423), 1034-10434.
  2. Justel, A., Peña, D., & Zamar, R. 1997. A multivariate Kolmogorov-Smirnov test of goodness of & Probability Letters Statistics, 35(3), 251-259.5. Nelsen 1999. R. B. Introduction. An Introduction to Copulas, Springer New York.6. Bouyé, E., Durrleman, V., Nikeghbali, A., Riboulet, G., & Roncelli, T. 2000. Copulas for finance-a reading guide and some applications.7. Frey, J. D. R., McNeil, A. J., Nyfeler, M. 2001. Copulas and credit models. Risk, 10(111114.10).8. Kim, G., Silvapulle, M. J., & Silvapulle, P. 2007. Comparison of semiparametric and parametric methods estimating copulas. Computational Statistics & Data Analysis, 51(6), 2836-2850.9. Genest, C., & Favre, A. C. 2007. Everything you always wanted to know about copula modeling but were afraid to ask. Journal of hydrologic engineering, 12(4), 347-368.10. Salvadori, G., De Michele, C., Kottegoda, N. T., & Rosso, R. 2007. Extremes in nature: an approach using copulas, Springer Science & Business Media.11. Berg, Daniel 2009. Copula goodness-of-fit testing: an overview and power comparison. The European Journal of Finance., 15, 675-701.12. Fermanian 2005. J. D. Goodness-of-fit tests for copulas. Journal of multivariate analysis, 95(1), 119-152.13. Genest, C., & Rémillard, B. 2008. Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models. In Annals de l'Institut Henri Poincaré, Probabilities et Statistiques, 44(6), 1096-1127.14. Genest, C., Rémillard, B., Beaudoin, D. 2009. Goodness-of-fit tests for copulas: A review and a power study. Insurance: Mathematics and economics, 44(2), 199-213.15. Huard, D., Évin, G., Favre, A. C. 2006. Bayesian copula selection. Computational Statistics & Data in Analysis, 51(2), 809-822.16. Jordanger, L. A., & Tjostheim, D. 2014. Model selection of copulas: AIC versus a cross validation copula information criterion. Statistics & Probability Letters, 92, 249-255.17. Kojadinovic, I., Yan, J., & Holmes, M. 2011. Fast large-sample goodness-of-fit tests for copulas. Statistica Sinica, 841-871.18. Kojadinovic, I., & Yan, J. 2011. A