A0727
Title: Fast multilevel functional principal component analysis
Authors: Erjia Cui - University of Minnesota (United States) [presenting]
Abstract: Fast multilevel functional principal component analysis (fast MFPCA) is introduced, which scales up to high dimensional functional data measured at multiple visits. The new approach is orders of magnitude faster than the original MFPCA and achieves comparable estimation accuracy. Methods are motivated by the National Health and Nutritional Examination Survey (NHANES), which contains minute-level physical activity information of more than 10,000 participants over multiple days and 1440 observations per day. While MFPCA takes more than five days to analyze these data, fast MFPCA takes less than five minutes. A theoretical study of the proposed method is also provided. The associated function mfpca.face() is available in the R package refund.
