Over the last 20 years, comprehensive strategies for treating measurement error in complex
models and accounting for the use of extra data to estimate measurement error parameters …

This hands-on guide is primarily intended to be used in undergraduate laboratories in the
physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces …

When evaluating the performance of quantitative models, dimensioned errors often are
characterized by sums-of-squares measures such as the mean squared error (MSE) or its …

Measurement error data or errors-in-variable data are often collected in many studies.
Natural criterion functions are often unavailable for general functional measurement error …

Model validation metrics have been developed to provide a quantitative measure that
characterizes the agreement between predictions and observations. In engineering design …

We describe a simulation-based method of inference for parametric measurement error
models in which the measurement error variance is known or at least well estimated. The …

If you search the web formeasurement uncertainty', you will obtain a list of some 14500
items. This confirms, if necessary, the pervasiveness of this concept. Curiously, I am not …

The Springer Series in Measurement Science and Technology comprehensively covers the
science and technology of measurement, addressing all aspects of the subject from the …

The primary goal of this book is to provide a recipe explaining the functioning of data fitting
via least squares and the emphasis here is on practical matters, not on theoretical problems …

The major objective of this book is to give methods for estimating errors and uncertainties of
real measurements: measurements that are performed in industry, commerce, and …