This dissertation presents the development of a novel multivariate model based on copula dependence functions and common risk factors. Key accomplishments include procedures for fitting of model parameters to data, in addition to an efficient means of sampling from the resulting distribution. Copulas are an interesting result from the study of probability metric spaces that possess the ability of generating multivariate distributions coupled together from their univariate marginals. The work herein adds to the current copula literature, a new multivariate copula framework with reduced parameter estimation burden, by utilizing a common risk factor approach. Presently, there are only three broad categories of copula families that dominate in scholarly works: Elliptical copulas due to their familiarity in current statistical models (e.g. the Gaussian copula); Archimedean copulas due to their mathematical tractability; and Extreme Value copulas which are useful when the subject matter being studied is extreme valued. So, although the potential for the adoption of copulas in statistical analysis remains high, the actual implementation of copula models is often limited to these three copula families. Additionally, compared to bivariate copulas there is also a deficiency in the actual application of multivariate copula models. The current multivariate model is significant in that it offers an alternate multivariate copula model with a straightforward sampling procedure. The use of this model can aid in the further adoption of copulas in statistical dependence applications.
|Advisor:||Dorp, Johan R. van|
|Commitee:||Campos-Nanez, Enrique, Deason, Jonathan P., Mazzuchi, Thomas A., Roncace, Robert A.|
|School:||The George Washington University|
|Department:||Engineering Mgt and Systems Engineering|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 73/01, Dissertation Abstracts International|
|Keywords:||Copula dependence functions, Generalized diagonal bands, Power generating densities, Uncertainty analysis|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be