Measurement error arises when the observed data deviate from true values due to inaccuracies in measurement processes, potentially leading to biased estimates and ...

We consider quasilikelihood models when some of the predictors are measured with error. In many cases, the true but fallible predictor is impossible to measure, and ...

We describe two approaches to instrumental variable estimation in binary regression measurement error models. The methods entail constructing approximate mean models ...

Temperature is by far the most commonly measured physical parameter. With so many new ideas for connected devices in the works for consumer and industrial applications, you often need high-accuracy ...