کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1155657 | 958755 | 2013 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Asymptotic normality of the principal components of functional time series
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات (عمومی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Asymptotic normality of the principal components of functional time series Asymptotic normality of the principal components of functional time series](/preview/png/1155657.png)
چکیده انگلیسی
We establish the asymptotic normality of the sample principal components of functional stochastic processes under nonrestrictive assumptions which admit nonlinear functional time series models. We show that the aforementioned asymptotic depends only on the asymptotic normality of the sample covariance operator, and that the latter condition holds for weakly dependent functional time series which admit expansions as Bernoulli shifts. The weak dependence is quantified by the condition of L4L4-mm-approximability which includes all functional time series models in practical use. We also demonstrate convergence of the cross covariance operators of the sample functional principal components to their counterparts in the normal limit.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Stochastic Processes and their Applications - Volume 123, Issue 5, May 2013, Pages 1546–1562
Journal: Stochastic Processes and their Applications - Volume 123, Issue 5, May 2013, Pages 1546–1562
نویسندگان
Piotr Kokoszka, Matthew Reimherr,