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Activity Number:
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600
- Less Can Be More: Smart Sampling in Data and Engineering Sciences
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #305133
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Presentation 1
Presentation 2
Presentation 3
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Title:
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Varying Coefficient Frailty Models with Applications in Single Molecular Experiments
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Author(s):
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Jiazhao Zhang* and Ying Hung and Tirthankar Dasgupta
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Companies:
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Rutgers University and Rutgers University and Rutgers University
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Keywords:
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Computer Experiments;
Cox Model ;
Frailty Model
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Abstract:
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Motivated by an analysis of single molecular experiments in the study of T cell signaling, a new model called varying coefficient frailty model is proposed. Frailty models have been extensively studied but not the generalization to non-constant coefficients. We introduce a modified EM algorithm with a local polynomial kernel smoothing technique to estimate the unknown parameters. Theoretical properties of the estimators are derived along with discussions on the asymptotic bias-variance trade-off. The finite sample performance is examined by simulation studies. The proposed method is implemented for the analysis of T cell signaling. The fitted varying coefficient model provides a rigorous quantification of an early and rapid impact on T cell signaling from the accumulation of bond lifetime, which can shed new light on the fundamental understanding of how T cells initiate immune responses.
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Authors who are presenting talks have a * after their name.
