  Motivated by applications to water quality monitoring using fluorescence
spectroscopy, we develop the source apportionment model for high dimensional
profiles of dissolved organic matter (DOM). We describe simple methods to
estimate the parameters of a linear source apportionment model, and show how
the estimates are related to those of ordinary and generalized least squares.
Using this least squares framework, we analyze the variability of the
estimates, and we propose predictors for missing elements of a DOM profile. We
demonstrate the practical utility of our results on fluorescence spectroscopy
data collected from the Neuse River in North Carolina.
