Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 2 of 2
Full-Text Articles in Statistical Methodology
Data-Adaptive Kernel Support Vector Machine, Xin Liu
Data-Adaptive Kernel Support Vector Machine, Xin Liu
Electronic Thesis and Dissertation Repository
In this thesis, we propose the data-adaptive kernel Support Vector Machine (SVM), a new method with a data-driven scaling kernel function based on real data sets. This two-stage approach of kernel function scaling can enhance the accuracy of a support vector machine, especially when the data are imbalanced. Followed by the standard SVM procedure in the first stage, the proposed method locally adapts the kernel function to data locations based on the skewness of the class outcomes. In the second stage, the decision rule is constructed with the data-adaptive kernel function and is used as the classifier. This process enlarges …
On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, Daniel Prawira
On The Estimation Of Penetrance In The Presence Of Competing Risks With Family Data, Daniel Prawira
Electronic Thesis and Dissertation Repository
In family studies, we are interested in estimating the penetrance function of the event of interest in the presence of competing risks. Failure to account for competing risks may lead to bias in the estimation of the penetrance function. In this thesis, three statistical challenges are addressed: clustering, missing data, and competing risks. We proposed the cause-specific model with shared frailty and ascertainment correction to account for clustering and competing risks along with ascertainment of families into study. Multiple imputation is used to account for missing data. The simulation study showed good performance of our proposed model in estimating the …