Yao-San Lin

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This article proposes a procedure for small sample regression, systematically using the concept of robust Bayesian inference and a contaminated prior. The approach explores the possible domain of population information and attempts to estimate regression parameters further. A data augmentation step included in the procedure works to enlarge the original(More)
Science learned models based on limited data are usually fragile, researchers suggest the adoption of virtual samples to improve the prediction model. In this study, nonparametric statistical tool, Kolmogorov-Smirnov test, is introduced to examine the distribution of virtual samples without any assumption about the underlying population. The examination(More)
Executing pilot runs before mass production is a common strategy in manufacturing systems. Using the limited data obtained from pilot runs to shorten the lead time to predict future production is this worthy of study. Since a manufacturing system is usually comprehensive, Artificial Neural Networks are widely utilized to extract management knowledge from(More)
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