| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 99 === Microarray data analysis has widely used in biological studies. However, it is common that there are missing values in microarray data, which affects the result of analysis. As many downstream analysis methods require complete datasets, missing value estimation has been an important pre-processing step in the microarray analysis. Among the existed missing value imputation methods, the regression-based methods are very popular. Many algorithms are developed for reconstructing these missing values. In this study, we propose a James-Stein type modified estimator for the regression coefficients. We compare the performance of the conventional imputations and the James-Stein type adjusted imputation method, our approach shows better performance than the others on various datasets.
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