کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1147922 957808 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On multivariate Gaussian copulas
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
On multivariate Gaussian copulas
چکیده انگلیسی

Gaussian copulas are handy tool in many applications. However, when dimension of data is large, there are too many parameters to estimate. Use of special variance structure can facilitate the task. In many cases, especially when different data types are used, Pearson correlation is not a suitable measure of dependence. We study the properties of Kendall and Spearman correlation coefficients—which have better properties and are invariant under monotone transformations—used at the place of Pearson coefficients. Spearman correlation coefficient appears to be more suitable for use in such complex applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 139, Issue 11, 1 November 2009, Pages 3942–3946
نویسندگان
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