8 papers
A Computationally Efficient Learning of Artificial Intelligence System Reliability Considering Error Propagation
Fenglian Pan, Yinwei Zhang, Yili Hong +2
Artificial Intelligence (AI) systems are increasingly prominent in emerging smart cities, yet their reliability remains a critical concern. These systems typically operate through…
What Quality Engineers Need to Know about Degradation Models
Jared M. Clark, Jie Min, Mingyang Li +5
Degradation models play a critical role in quality engineering by enabling the assessment and prediction of system reliability based on data. The objective of this paper is to prov…
Modeling Spatially Correlated Failure-time Data Under Two Distance Functions with an Application to Titan GPU Data
Jared M. Clark, Jie Min, Yueyao Wang +2
One common approach to statistical analysis of spatially correlated data relies on defining a correlation structure based solely on unknown parameters and the physical distance bet…
The Use of Variational Inference for Lifetime Data with Spatial Correlations
Yueyao Wang, Yili Hong, Laura Freeman +1
Lifetime data with spatial correlations are often collected for analysis in modern engineering, clinical, and medical applications. For such spatial lifetime data, statistical mode…
StatLLM: A Dataset for Evaluating the Performance of Large Language Models in Statistical Analysis
Xinyi Song, Lina Lee, Kexin Xie +3
The coding capabilities of large language models (LLMs) have opened up new opportunities for automatic statistical analysis in machine learning and data science. However, before th…
Performance Evaluation of Large Language Models in Statistical Programming
Xinyi Song, Kexin Xie, Lina Lee +10
The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the v…