Zobrazeno 1 - 10
of 293
pro vyhledávání: '"Du Pang"'
Publikováno v:
Frontiers in Molecular Neuroscience, Vol 15 (2022)
Mitosis and meiosis are crucial life activities that transmit eukaryotic genetic information to progeny in a stable and orderly manner. The formation and appearance of chromosomes, which are derived from chromatin, are the preconditions and signs of
Externí odkaz:
https://doaj.org/article/9d9474b3f7d74b2689cbdafbdd6bb995
Multi-sensor data that track system operating behaviors are widely available nowadays from various engineering systems. Measurements from each sensor over time form a curve and can be viewed as functional data. Clustering of these multivariate functi
Externí odkaz:
http://arxiv.org/abs/2401.02557
Renewable energy is critical for combating climate change, whose first step is the storage of electricity generated from renewable energy sources. Li-ion batteries are a popular kind of storage units. Their continuous usage through charge-discharge c
Externí odkaz:
http://arxiv.org/abs/2212.05515
We propose inferential tools for functional linear quantile regression where the conditional quantile of a scalar response is assumed to be a linear functional of a functional covariate. In contrast to conventional approaches, we employ kernel convol
Externí odkaz:
http://arxiv.org/abs/2202.11747
Motivated by a hemodialysis monitoring study, we propose a logistic model with a functional predictor, called the Sparse Functional Logistic Regression (SFLR), where the corresponding coefficient function is {\it locally sparse}, that is, it is compl
Externí odkaz:
http://arxiv.org/abs/2106.10583
Publikováno v:
Statistica Sinica, 2023 Jan 01. 33(2), 1047-1068.
Externí odkaz:
https://www.jstor.org/stable/27249951
Akademický článek
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We consider the problem of comparing probability densities between two groups. A new probabilistic tensor product smoothing spline framework is developed to model the joint density of two variables. Under such a framework, the probability density com
Externí odkaz:
http://arxiv.org/abs/1911.02171
Optimal Penalized Function-on-Function Regression under a Reproducing Kernel Hilbert Space Framework
Publikováno v:
Journal of the American Statistical Association, 113:524, 1601-1611
Many scientific studies collect data where the response and predictor variables are both functions of time, location, or some other covariate. Understanding the relationship between these functional variables is a common goal in these studies. Motiva
Externí odkaz:
http://arxiv.org/abs/1902.03674
Akademický článek
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