Publications by authors named "Lianne A Sheppard"
A novel principal component analysis for spatially misaligned multivariate air pollution data.
J R Stat Soc Ser C Appl Stat
January 2017
Article Synopsis
- Researchers are introducing new methods for predictive (sparse) PCA to analyze air pollution data that may not align spatially.
- These methods aim to accurately identify principal component loading vectors that capture variability in the data and predict scores for locations lacking direct measurements.
- The approach has been tested with simulated data and applied to real particulate matter data from EPA monitors, enabling better insights into pollutant mixtures and their health impacts in cohort studies.