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Structured regression models for high-dimensional spatial spectroscopy data. (English) Zbl 1380.62248

Processing and analysis of microscopy data is a very active area of research with numerous applications in various scientific disciplines. The authors present a functional model for analysing high-dimensional spectra for the purpose of noise reduction and prediction. They consider the effectiveness of the approach in three settings: in vivo and ex vivo Raman data from a fracture healing experiment, and using NMR data in a lipoprotein concentration study.

MSC:

62P10 Applications of statistics to biology and medical sciences; meta analysis
62G08 Nonparametric regression and quantile regression
62M15 Inference from stochastic processes and spectral analysis
62M20 Inference from stochastic processes and prediction
62M30 Inference from spatial processes
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