Robust methods of parameter estimation are often employed in multivariate applications where gross errors aaect the data, however robust methods commonly lack pre-and post-analysis measures enjoyed by least squares estimation. In terms of pre-analysis, we describe a mathematically rigorous method for determining redundancy numbers based on L1-norm minimization and for post-analysis we outline a...

Process data measurements are important for process monitoring, control and optimization. However, process data may be deteriorated by gross errors in measurements. Therefore, it is significant to detect and estimate gross errors with data reconciliation. Meanwhile, in any modern petrochemical plant, the plant-wide mass data derived from process data rendering the real conditions of manufacturi...

A prime goal of quantum tomography is to provide quantitatively rigorous characterization of quantum systems, be they states, processes or measurements, particularly for the purposes of trouble-shooting and benchmarking experiments in quantum information science. A range of techniques exist to enable the calculation of errors, such as Monte-Carlo simulations, but their quantitative value is arg...

Error is an inevitable part of life and cannot be completely eliminated, but it can be minimized. A root cause analysis is a technique for understanding the systematic error causes that is involved beyond a person or people to implement an errors and including field and environmental causes of errors when occur in this situation too. An important factor of an error occurrence is a root cause (c...