Original paper
Likelihood inference for Archimedean copulas in high dimensions under known margins
Abstract
Explicit functional forms for the generator derivatives of well-known one-parameter Archimedean copulas are derived. These derivatives are essential for likelihood inference as they appear in the copula density, conditional distribution functions, and the Kendall distribution function. They are also required for several asymmetric extensions of Archimedean copulas such as Khoudraji-transformed Archimedean copulas. Availability of the generator...
Paper Details
Title
Likelihood inference for Archimedean copulas in high dimensions under known margins
Published Date
Sep 1, 2012
Volume
110
Pages
133 - 150
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