Methods for handling measurement error and sources of variation in functional data models
The overall theme of this thesis work concerns the problem of handling measurement error and sources of variation in functional data models. The first part introduces a wavelet-based sparse principal component analysis approach for characterizing the variability of multilevel functional data that ar...
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| Language: | English |
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2015
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| Online Access: | https://doi.org/10.7916/D8M907CJ |