A heteroscedasticity diagnostic of a regression analysis with copula dependent random variables
Author:
Affiliation:
1. Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
2. Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering, STU Bratislava, Slovakia
Publisher
Institute of Mathematical Statistics
Subject
Statistics and Probability
Reference29 articles.
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2. Acar, E. F., Azimaee, P. and Hoque, Md. E. (2019). Predictive assessment of copula models. Canadian Journal of Statistics 47, 8–26.
3. Alqawba, M., Diawara, N. and Kim, J. (2019). Copula directional dependence of discrete time series marginals. Communications in Statistics-Simulation and Computation, 1–18.
4. Ando, T., Konishi, S. and Imoto, S. (2008). Nonlinear regression modeling via regularized radial basis function networks. Journal of Statistical Planning and Inference 138, 3616–3633.
5. Awad, M. and Khanna, R. (2015). Support vector regression. Efficient learning machines, 67–80.
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