期刊
STATISTICS & PROBABILITY LETTERS
卷 138, 期 -, 页码 165-170出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.spl.2018.03.007
关键词
Local linear smoothers; Non-dense functional data; Dense functional data; Ultra-dense functional data; Mixture weighting schemes
资金
- United States National Science Foundation [DMS-1613018, DMS-1512975]
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1512975] Funding Source: National Science Foundation
We propose optimal weighting schemes for both mean and covariance estimations for functional data based on local linear smoothing such that the L-2 rate of convergence is minimized. These schemes can self-adjust to the sampling plan and lead to practical improvements. (C) 2018 Elsevier B.V. All rights reserved.
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