Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Artificial neural network & Control theory. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Laboratory Simulation of Charge Exchange-Produced X-ray Emission from Comets

Abstract: In laboratory experiments using the engineering spare microcalorimeter detector from the ASTRO-E satellite mission, we recorded the x-ray emission of highly charged ions of carbon, nitrogen, and oxygen, which simulates charge exchange reactions between heavy ions in the solar wind and neutral gases in cometary comae. The spectra are complex and do not readily match predictions. We developed a charge exchange emission model that successfully reproduces the soft x-ray spectrum of comet Linear C/1999 S4, observed with the Chandra X-ray Observatory.

Optimal sufficient dimension reduction in regressions with categorical predictors

Abstract: Though partial sliced inverse regression (partial SIR: Chiaromonte et al. [2002. Sufficient dimension reduction in regressions with categorical predictors. Ann. Statist. 30, 475–497]) extended the scope of sufficient dimension reduction to regressions with both continuous and categorical predictors, its requirement of homogeneous predictor covariances across the subpopulations restricts its application in practice. When this condition fails, partial SIR may provide misleading results. In this article, we propose a new estimation method via a minimum discrepancy approach without this restriction. Our method is optimal in terms of asymptotic efficiency and its test statistic for testing the dimension of the partial central subspace always has an asymptotic chi-squared distribution. It also gives us the ability to test predictor effects. An asymptotic chi-squared test of the conditional independence hypothesis that the response is independent of a selected subset of the continuous predictors given the remaining predictors is obtained.

A probabilistic and statistical view of fuzzy methods

Abstract: Fuzzy set theory has primarily been associated with control theory and with the representation of uncertainty in applications in artificial intelligence. More recently, fuzzy methods have been proposed as alternatives to traditional statistical methods in statistical quality control, linear regression, and forecasting, among other areas. We review some basic concepts of fuzzy methods, point out some philosophical and practical problems, and offer simpler alternatives based on traditional probability and statistical theory. Applications in control theory and statistical quality control serve as our primary examples.