Principal Data Scientist and Software Developer, Eigenvector Research, Inc.
Nate Watson holds BS, MS and PhD degrees in analytical chemistry and other applied disciplines earned between 1999 and 2017. He has nearly three decades of experience using chemometric methods to answer analytical questions.
His research interests are varied. He particularly enjoys bridging complicated scientific and mathematical concepts into language that is easily understood by end users and technicians.
He is married and has four children. He currently resides in Western Montana.
A technical white paper deriving the classical least squares (CLS) and weighted least squares (WLS) models and showing how generalized least squares (GLS) and extended least squares (ELS) extend CLS to provide clutter suppression for characterized interference signals in spectroscopic and hyperspectral measurements.
