153 research outputs found
Expert forecasting with and without uncertainty quantification and weighting: What do the data say?
No full textPost-2006 expert judgment data has been extended to 530 experts assessing 580 calibration variables from their fields. New analysis shows that point predictions as medians of combined expert distributions outperform combined medians, and medians of performance weighted combinations outperform medians of equal weighted combinations. Relative to the equal weight combination of medians, using the medians of performance weighted combinations yields a 65% improvement. Using the medians of equally weighted combinations yields a 46% improvement. The Random Expert Hypothesis underlying all performance-blind combination schemes, namely that differences in expert performance reflect random stressors and not persistent properties of the experts, is tested by randomly scrambling expert panels. Generating distributions for a full set of performance metrics, the hypotheses that the original panels’ performance measures are drawn from distributions produced by random scrambling are rejected at significance levels ranging from E−6 to E−12. Random stressors cannot produce the variations in performance seen in the original panels. In- and out-of-sample validation results are updated.Applied Probabilit
Temptation and Virtue
No full textThis project investigates people's perceptions of agents who are deliberate and choose different options in moral dilemmas
Contributions to Modeling and Inference for k-Level Step Stress Accelerated Life Tests under Progressive Type-I Censoring with Lifetimes for a Log-Location Scale Family
No full textThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.In reliability engineering, the accelerated life test is not only becoming increasingly popular but also absolutely necessary. This is due to the rapid yield of information about the lifetime distribution of highly reliable products and devices in shorter time periods, which it achieves by conducting the life test at more extreme stress levels than normal operating conditions. Through extrapolation, the lifetime distribution at the usage stress can be estimated with an appropriate regression model. In our work, we inspect a number of modeling and inferential problems related to censored lifetime data from log-location-scale distribution under the step-stress accelerated life tests (ssALT). First, we investigate the inference of a progressively Type-I censored k-level step-stress accelerated life test when the lifetime of a test unit follows a log-location-scale family of distributions. Although simple and analytical, the popular exponential distribution lacks the model flexibility desired in practice due to the constraint of constant hazard rates. Pragmatically, Weibull or lognormal distributions, which are members of the log-location-scale family, demonstrate superior model fits. Therefore, our study is extended to consider the general log-location-scale family, and our inferential, prescriptive methods are illustrated using three popular lifetime distributions, including Weibull, lognormal, and log-logistic. The log-location-scale family provides stronger model flexibility, hence provides better fits and improves the reliability analysis considerably. Assuming that the location parameter is linearly linked to the (transformed) stress level (i.e., μi = α + βxi), an iterative algorithm is developed to estimate the regression parameters α and β along with the scale parameter σ. Subsequently, this allows the intermediate censoring to take place at the end of each stress level xi (viz.,τi, i = 1,...,k). Furthermore, using the exact distributions of the estimators, the Wald-type asymptotic 95% confidence interval and BCa bootstrap 95% confidence intervals for the respective parameters are obtained for comparison. Then, we determine the optimal stress duration times numerically under various design criteria based on Fisher's expected information, namely D-optimality, T-optimality, C-optimality, A-optimality, M-optimality, and E-optimality. The effect of intermediate censoring proportion on design efficiency is also assessed computationally with a real engineering case study into analyzing the reliability characteristic of a solar lighting device. Next, we study the statistical inference for progressively Type-I censored k-level step-stress accelerated life tests under interval monitoring, with the lifetime of a test unit following a log-location scale family distributions, and compared simulation studies with previous continuous monitoring results. Finally, we formulate the cost model function for the constrained optimal designs under simple ssALT and then define five design criteria based on Fisher's expected information and study the efficiency of optimality models under constrained and unconstrained settings.Management Science and Statistic
Pragmatics and Accessibility in Referential Communication
No full textThis study evaluates whether listeners are sensitive to the pragmatics and accessibility of referential expressions in ambiguous language contexts. Participants will be presented with a random grid of 20 words and specific words as "clues." They will attempt to identify two words that the clues might refer to on the board. Clues will vary in pragmatics and accessibility and we will test whether these variables influence the accuracy of the participant in identifying the intended word pairs. We will also test how the accessibility of potential guesses affects the likelihood of their selection
7.1.2 System of Systems Engineering Facilitates Integration of Large Scale Complex Systems
No full text2024.08.01 study
No full textAre people more likely to consider a claim of fact to be false if discrepancies between the claim and the ground truth cause an outcome that wouldn’t have occurred if the claim had been perfectly accurate? If so, is this influenced by the magnitude of the downstream outcome and/or whether the downstream outcome was good or bad
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