Çiğdem GÜLÖKSÜZ TOPÇU

Comparison of Some Selection Criteria for Selecting Bivariate Archimedean Copulas

Genellikle, veriyi modelleyen uygun iki boyutlu Arşimedyen kapula fonksiyonunu seçerken Akaike Bilgi Kriteri (AIC), Bayesçi Bilgi Kriteri (BIC) ile en küçük uzaklık seçim kriteri olarak kullanılır. Bu çalışmada, bu seçim kriterlerinin kapula seçimindeki performansları simulasyon çalışması ile incelenmiştir.

İki Boyutlu Arşimedyen Kapulalar İçin Bazı Seçim Kriterlerinin Karşılaştırılması

Commonly, while selecting an appropriate bivariate Archimedean copula function that models data, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and minimum distance (MD) are used as a selection criterion. In this study, the performances of these criteria for selecting copula function are investigated by some simulation studies.

PDF

___

Atkinson, A., 1969. A test for discriminating between models. Biometrika 56, 337-341
Atkinson, A., 1970. A method for discriminating between models. Journal of the Royal statistical Society, Series B32, 323-353.
Belgorodski, N., 2010. Selecting pair copula families for regular vines with application to the multivariate analysis of European stock market indices. Master Thesis, Technische Universität München.
Clayton, D.G., 1978. A Model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika, 65, 141-151.
Cox, D.R., 1962. Further Results on tests of seperate families of hypotheses. Journal of the Royal Statistical Society, Series B24, 406-424.
Durrleman, V., Nikeghbali, A., and Roncalli, T., 2000. Which copula is the right one? Technical Report Groupe de Researche operationnelle Credit- Lyonnois.
Frank, M.J., 1979. On the simultaneous associativity of F(x,y) and x+y-F(x,y). Aequationes Mathematicae, 19, 194-226.
Frees, W.E. and Valdez, A.E., 1997. Understanding relationships using copulas. 32nd. Actuarial Research Conference, 6-8 August at University of Calgary, Albert ,Canada.
Genest, C., and Rivest, L.P., 1993. Statistical inference procedures for bivariate archimedean copulas. Journal of the American Statistical Association Theory and Methods ,88, No: 423
Genest, C., Rémillard, B. and Beaudoin, D., 2009. goodness-of-fit tests for copulas: A review and apower study. Insurance: Mathematics and Economics, 44,199-213.
Grønneberg, S., and Hjort N.L., 2014. The Copula Information Criteria. Scandinavian Journal of Statistics, 41,436-459.
Gumbel, E.J., 1960. Bivariate exponential distributions. Journal of the American Statistical Association, 55, 698-707.
Huard, D.,Evin, G., and Favre, A.C., 2006. Bayesian copula selection. Computational Statistics&Data Analysis, 51(2), 809-822.
Joe, H., 1997. Multivariate Models and Dependence Concepts. Chapman & Hall Ltd. Nelsen, R., 2006. An Introduction to Copulas. Springer, NewYork.
R-Development Core Team (2012). R: A Language and Environment for Statistical Computing (computer software). Available from: http://www.R-project.org. Sklar, A., 1959. Fonctions de repartition a n dimensions et leurs marges., Publications del'Institut de Statistique de l'Universite de Paris,8, 229-231.Sklar,
A., 1973. Random variables, joint distribution functions and copulas. Kybernetika, 9,449-460.
Schweizer, B., and Sklar, A. 1983. Probabilistic Metric Spaces. North-Holland, New York.
Wolfowitz, J., 1957. The minimum distance method. Ann. Math. Statist., 28, 75-87.