Baojiang CHEN, Ao YUAN, Grace Y. YI, Variable selection for proportional hazards models with high-dimensional covariates subject to measurement error, The Canadian Journal of Statistics / La Revue ...

S. M. Schennach, Yingyao Hu, Nonparametric Identification and Semiparametric Estimation of Classical Measurement Error Models Without Side Information, Journal of the ...

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

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 ...

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

For estimates among U.S. adults on 28 benchmark variables, opt-in samples 1, 2 and 3 had average absolute errors of 6.4, 6.1 and 5.0, respectively, for an overall average of 5.8 percentage points.

It supports the two-point calibration practice to minimize errors, particularly at lower concentrations, and recommends measures such as improved aerosol systems and automation to enhance calibration ...