Joint adaptive mean-variance regularization and variance stabilization of high dimensional data
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Publication:693237
DOI10.1016/j.csda.2012.01.012zbMath1252.62036OpenAlexW1984872583WikidataQ34308629 ScholiaQ34308629MaRDI QIDQ693237
J. Sunil Rao, Jean-Eudes Dazard
Publication date: 7 December 2012
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2012.01.012
regularizationnormalizationbioinformaticsinadmissibilityshrinkage estimators\texttt{R package MVR}variance stabilization
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- Estimating the Number of Clusters in a Data Set Via the Gap Statistic
- On testing the significance of sets of genes
- Resampling-based multiple testing for microarray data analysis (With comments)
- The control of the false discovery rate in multiple testing under dependency.
- Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
- Significance analysis of microarrays applied to the ionizing radiation response
- Variance Estimation in the Analysis of Microarray Data
- Robust Locally Weighted Regression and Smoothing Scatterplots
- Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
- Empirical Bayes Analysis of a Microarray Experiment
- Detecting Differentially Expressed Genes in Microarrays Using Bayesian Model Selection
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Strong Control, Conservative Point Estimation and Simultaneous Conservative Consistency of False Discovery Rates: A Unified Approach
- Operating Characteristics and Extensions of the False Discovery Rate Procedure
- The Optimal Discovery Procedure: A New Approach to Simultaneous Significance Testing
- A Comparison of Parametric and Nonparametric Methods for Normalising cDNA Microarray Data
- Optimal Shrinkage Estimation of Variances With Applications to Microarray Data Analysis
- Improved statistical tests for differential gene expression by shrinking variance components estimates
- Statistical significance for genomewide studies
- Spike and Slab Gene Selection for Multigroup Microarray Data