کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5076945 | 1374108 | 2010 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison of three semiparametric methods for estimating dependence parameters in copula models
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Comparison of three semiparametric methods for estimating dependence parameters in copula models Comparison of three semiparametric methods for estimating dependence parameters in copula models](/preview/png/5076945.png)
چکیده انگلیسی
Three semiparametric methods for estimating dependence parameters in copula models are compared, namely maximum pseudo-likelihood estimation and the two method-of-moment approaches based on the inversion of Spearman's rho and Kendall's tau. For each of these three asymptotically normal estimators, an estimator of their asymptotic (co)variance is stated in three different situations, namely the bivariate one-parameter case, the multivariate one-parameter case and the multivariate multiparameter case. An extensive Monte Carlo study is carried out to compare the finite-sample performance of the three estimators under consideration in these three situations. In the one-parameter case, it involves up to six bivariate and four-variate copula families, and up to five levels of dependence. In the multiparameter case, attention is restricted to trivariate and four-variate normal and t copulas. The maximum pseudo-likelihood estimator appears as the best choice in terms of mean square error in all situations except for small and weakly dependent samples. It is followed by the method-of-moment estimator based on Kendall's tau, which overall appears to be significantly better than its analogue based on Spearman's rho. The simulation results are complemented by asymptotic relative efficiency calculations. The numerical computation of Spearman's rho, Kendall's tau and their derivatives in the case of copula families for which explicit expressions are not available is also investigated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Insurance: Mathematics and Economics - Volume 47, Issue 1, August 2010, Pages 52-63
Journal: Insurance: Mathematics and Economics - Volume 47, Issue 1, August 2010, Pages 52-63
نویسندگان
Ivan Kojadinovic, Jun Yan,