The research will improve measurement science by developing new statistical calibration methodology for precision instruments. Calibration with errors in the standards will be examined through the errors-in-variables regression problem. Multivariate calibration problems in analytical chemistry will be studied through statistical models. New data analytic alternatives to hypothesis testing will be provided by combining parametric and nonparametric aspects in one model. This semiparametric approach will be used to estimate the percentage of contamination in a sample and provide asymptotic distributions.
