کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1145172 1489649 2016 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Best estimation of functional linear models
ترجمه فارسی عنوان
بهترین تخمین مدل های خطی کاربردی
کلمات کلیدی
تحلیل داده های کاربردی. فضاهای Sobolev؛ مدل های خطی؛ اندازه گیری های مکرر؛ قضیه گوس مارکف؛ قضیه بازنمایی Riesz ؛ بهترین برآوردگر بیطرف خطی
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
چکیده انگلیسی

Observations that are realizations of some continuous process are frequently found in science, engineering, economics, and other fields. In this paper, we consider linear models with possible random effects and where the responses are random functions in a suitable Sobolev space. In particular, the processes cannot be observed directly. By using smoothing procedures on the original data, both the response curves and their derivatives can be reconstructed, both as an ensemble and separately. From these reconstructed functions, one representative sample is obtained to estimate the vector of functional parameters. A simulation study shows the benefits of this approach over the common method of using information either on curves or derivatives. The main theoretical result is a strong functional version of the Gauss–Markov theorem. This ensures that the proposed functional estimator is more efficient than the best linear unbiased estimator (BLUE) based only on curves or derivatives.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 151, October 2016, Pages 54–68
نویسندگان
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