کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1145252 1489653 2016 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Estimation of eigenvalues, eigenvectors and scores in FDA models with dependent errors
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
پیش نمایش صفحه اول مقاله
Estimation of eigenvalues, eigenvectors and scores in FDA models with dependent errors
چکیده انگلیسی

Observations in functional data analysis (FDA) are often perturbed by random noise. In this paper we consider estimation of eigenvalues, eigenfunctions and scores for FDA models with weakly or strongly dependent error processes. As it turns out, the asymptotic distribution of estimated eigenvalues and eigenfunctions does not depend on the strength of dependence in the error process. In contrast, the rate of convergence and the asymptotic distribution of estimated scores differ distinctly between the cases of short and long memory. Simulations illustrate the asymptotic results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 147, May 2016, Pages 218–233
نویسندگان
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