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We employ network metrics on relational variables of interest to control for econometric estimation bias, inefficiency and inferential problems from non-spherical, network induced disturbances in sampled, unknown behaviorally driven networks. Our analysis follows a two-step procedure to establish a conceptual baseline and then integrate real-world data and questions pertinent for statistical inference...
Computational analysis of appearance and morphology patterns of cells offers good potential to quantify the effect of candidate drug compounds on a cell population relative to the control in high throughput phenotypic screening. Extracting accurate morphometric information for each individual cell requires reliable detection and segmentation of object boundaries. For some cell lines and under certain...
In this work, we described a powerful volume diagnosis and yield analysis framework called DiagBridge. DiagBridge enhances volume diagnosis results with sort and design data so as to present the volume diagnosis results in easy-to-understand metrics like yield loss estimation and failure rate estimation. We are already sharing these results with cross-functional teams and seeing various functional...
Information geometry is a new and increasing topic between statistics, estimation and differential geometry. Many amazing relationships between these domains were established through the last years. Unfortunately, it is not easy to find an easy approach to information geometry, which requires a deep understanding of differential geometry and statistics. The paper presents an easy readable introduction...
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