Homoscedastic controlled calibration model
Abstract
In the context of the usual calibration model, we consider the case in which the independent variable is unobservable, but a pre-fixed value on its surrogate is available. Thus, considering controlled variables and assuming that the measurement errors have equal variances we propose a new calibration model. Likelihood based methodology is used to estimate the model parameters and the Fisher information matrix is used to construct a confidence interval for the unknown value of the regressor variable. A simulation study is carried out to asses the effect of the measurement error on the estimation of the parameter of interest. This new approach is illustrated with an example.
Cite
@article{arxiv.0802.0691,
title = {Homoscedastic controlled calibration model},
author = {Betsabé G. Blas Achic and Mônica C. Sandoval and Olga Satomi Yoshida},
journal= {arXiv preprint arXiv:0802.0691},
year = {2008}
}
Comments
LaTex, 21 pages. Includes 13 tables. Version published in Journal of Chemometrics, v. 21, p. 145-155, 2007