Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
نویسندگان
چکیده
Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
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عنوان ژورنال:
- Journal of computational biology : a journal of computational molecular cell biology
دوره 14 10 شماره
صفحات -
تاریخ انتشار 2007