Machine learning is a growing method for causal inference. In machine learning settings, prediction errors are a commonly overlooked problem that can bias results and lead to arbitrarily incorrect parameter estimates. We consider a two-stage model where (1) machine learning is used to predict...

In this, we argue that statistics is one of the fields of greatest significance for developing tools and techniques to find patterns in data and to give a greater understanding of them, as well as the most crucial for analyzing and calculating uncertainty. We provide a summary of several data...

Exploring moisture distribution, especially bound water content, is vital for studying and applying sludge dewatering. The differential scanning calorimetry (DSC) method has been extensively utilized for the quantitative characterization of moisture distribution in sludge. However, this method...

Problem definition. We present a continuous-time Bayesian model for managing inventory in a retail setting when inventory records are inaccurate. In our formulation, the inventory level and its record have separate dynamics. The former is driven by the demand and unobservable loss process while...

Products cannot be produced as perfect as nominal values due to errors in manufacturing and assembly processes. These complex errors eventually affect the function and performance of the finished products. This paper deals with how to minimize the overall errors when assembling each part which...

Extensive research has been conducted on the properties of quadratic forms in normal random variables, represented by the symbol Q here. However, analytical results on the square root of the quadratic form, √Q, are limited. The square root of the quadratic form is, for example, used in finance...

Using commuting data for Brisbane, Australia, we find that accounting for measurement error in travel times causes the magnitude of parameters in mode and location choice models to increase approximately three-fold and 30-40%, respectively. Errors appear to be somewhat systematic, with travel...

Measures based on self-assessments, which are increasingly important in empirical economic research, are plagued by measurement error. This paper presents the first attempt at measuring both revealed and self-reported reliability of individuals' answers on self-reports of latent characteristics....

This paper proposes a powerful alternative to the t-test of the null hypothesis that a coefficient in linear regression is equal to zero when a regressor is mismeasured. We assume there are two contaminated measurements of the regressor of interest. We allow the two measurement errors to be...