Uncertainty Quantification for Nonparametric Estimation of Probability Measures and Delay Differential Equations Driven by Colored Noise
Abstract
We have continued our joint investigations on the identification of thermal degradation using probabilistic models in reflectance spectroscopy. These were carried in continued collaboration with scientists at AFRL(Materials State Awareness and Supportability Branch, Air Force Research Lab, WPAFB 45433, USA) lead by Amanda K. Criner. Reflectance spectroscopy obtained from a thermally treated silicon nitride carbon based ceramic matrix composite was used to quantity the oxidation products SiO2 and SiN. Our estimation results indicate a distinguishable increase in the SiO2 present in the samples which were heat treated for 100 hours compared to 10 hours. In our consideration of several other problems of interest to DOD, we discuss two other problems where aggregate data is often mistreated as individual data. The problems, PBPK modeling and Food Chemistry Modlels and possible improvements in the associated inverse problems are discussed and summarized in separate papers.We propose in [11] a novel method which accounts for inter-individual variability in experiments where only unidentified individual data is available. Both parametric and nonparametric methods for estimating the distribution of parameters which vary among individuals are developed. These methods are illustrated using both simulated data, and data taken from a physiological experiment. Taking the approach outlined in [11] results in more accurate quantification of the uncertainty attributed to interindividual variability.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 09, 2018
- Accession Number
- AD1062811
Entities
People
- Harvey Banks
Organizations
- North Carolina State University