Abstract Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued
development and standardization of methodologies for biomarkers and has provided an …

Principal component analysis (PCA) has been used to study the pathogenesis of diseases.
To enhance the interpretability of classical PCA, various improved PCA methods have been …

We present a new method to estimate common-mode components (CMC) in global
positioning system (GPS) position time-series. The method ('CMC Imaging') is fully …

For multisource data, blocks of variable information from certain sources are likely missing.
Existing methods for handling missing data do not take structures of block-wise missing data …

Partial least squares (PLS) is a prominent solution for dimension reduction and high-
dimensional regressions. Recent prevalence of multidimensional tensor data has led to …

The ordinary singularity mapping (OSM) approach utilizing regular square window and
ignoring the representativeness of geochemical samples may not characterize the …

Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak
nationality is the highest‐risk group in Xinjiang. In this work, an effective computer‐aided …

Block-wise missing data are becoming increasingly common in high-dimensional
biomedical, social, psychological, and environmental studies. As a result, we need efficient …

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to
uncover the dominant patterns of variability within a population. Despite its ability to …

Electron backscatter diffraction is a widely used technique for nano-to micro-scale analysis
of crystal structure and orientation. Backscatter patterns produced by an alloy solid solution …