Nonlinear models of measurement errors are used to analyze and correct inaccuracies in data collection and interpretation.

In this work, we develop a new smooth backfitting method and theory for estimating additive nonparametric regression models when the covariates are contaminated by measurement errors. For this, we ...

Furthermore, developments in nonparametric identification have facilitated more flexible specifications in models confronting errors in variables, enabling robust applications in fields such as ...

Material testing requires a knowledge of how the factors of accuracy, repeatability and resolution. Find out more about measurement errors.

Measurement errors in exposure assessment are unavoidable, with residential radon exposure being no exception (Bäverstam and Swedjemark, 1991; Lubin et al., 1995), and induce bias on RR estimates.

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling ...