معرفی
Joseph Glaz is a Professor in the Department of Statistics at the University of Connecticut. His work focuses on applied probability and statistical methodology, particularly in scan statistics and related inference techniques.
- Contact: joseph.glaz@uconn.edu
- Phone: (860) 486-4193 (Storrs Campus)
Research highlights:
- Develops scan statistics for discrete, continuous, and conditional data frameworks
- Specializes in change-point detection for normal data mean/variance
- Innovates robust methods for outlier-prone datasets
- Extends scan statistics to network and graph structures
- Contributed to foundational texts like the Handbook of Scan Statistics
Publication trends include:
- Scan statistics for genomic data (Hi-C translocation detection)
- Nonparametric and Bayesian extensions of scan methods
- Approximations and inequalities for sequential testing
- Applications in quality control, medical imaging, and sensor networks
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