International Journal For Multidisciplinary Research

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Vector Autoregressive Model Using Non-Normal Copula Errors

Author(s) Beulah S William, Nimitha John
Country India
Abstract This article focuses on a bivariate vector autoregressive model of lag 1 with non-normal errors. We propose a bivariate error distribution using two identical marginals through a copula function. The copula used for the study is the Farlie-Gumbel-Morgenstern copula, which is considered to be one of the efficient class of copula in describing the dependence between two random variables. The model parameters are estimated using the method of inference functions for margins, and the finite sample properties of the model is illustrated through simulation studies. A real life example is considered to illustrate the applications of the proposed model. The adequacy of the copula model is examined using the two sample version of kolmogorov smirnov test statistic.
Keywords Vector autoregression, Copula Function, FGM copula, Inference Function for margins.
Field Mathematics > Statistics
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-19
Cite This Vector Autoregressive Model Using Non-Normal Copula Errors - Beulah S William, Nimitha John - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20508
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