Synthesizing the classical and inverse methods in linear calibration

This paper considers the problem of linear calibration and presents
two estimators arising from a synthesis of classical and inverse
calibration approaches. Their performance properties are analyzed
employing the small error asymptotic theory. Using the criteria of
bias and mean squared error, the proposed estimators along with the
traditional classical and inverse calibration are compared.
Finally, some remarks related to future work are placed.