Structural and predictive analyses with a mixed copula?based vector autoregression model
نویسندگان
چکیده
In this study, we introduce a mixed copula-based vector autoregressive (VAR) model for investigating the relationship between random variables. The one-step maximum likelihood estimation is used to obtain point estimates of parameters and copula parameters. More specifically, combine likelihoods marginal construct full function. simulation study confirm accuracy as well reliability proposed model. Various forms from combination Gaussian, Student's t, Clayton, Frank, Gumbel, Joe copulas are introduced. compared traditional VAR single models assess its performance. Furthermore, real data also conducted validate our method. As result, it found that provides accurate reliable results. Also, show if ignore complex nonlinear correlation errors, causes significant efficiency loss in parameter terms |Bias| MSE. application best fitting study.
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ژورنال
عنوان ژورنال: Journal of Forecasting
سال: 2022
ISSN: ['0277-6693', '1099-131X']
DOI: https://doi.org/10.1002/for.2902