Supplemental material
Journal of Computational and Graphical Statistics
Volume 28, 2019 - Issue 4
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Location of Several Outliers in Multiple-Regression Data Using Elemental Sets
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Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target
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Review: , Two Books on Regression Diagnostics; D. A. Belsley, E. Kuh, R. E. Welsch, Regression Diagnostics: Identifying Influential Data and Sources of Collinearity; R. D. Cook, Sanford Weisberg, Residuals and Influence in Regression
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Composite Likelihood Bayesian Information Criteria for Model Selection in High-Dimensional Data
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Regulation of epidermal growth factor receptor signaling in human cancer cells by microRNA-7.
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Regression Shrinkage and Selection via the Lasso
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Stabilizing the lasso against cross-validation variability
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Asymptotic Analysis of Robust LASSOs in the Presence of Noise With Large Variance
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Outlier detection in high-dimensional regression model
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Influence Diagnostics for High-Dimensional Lasso Regression
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HIGH-DIMENSIONAL INFLUENCE MEASURE
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The Dantzig selector: Statistical estimation when $p$ is much larger than $n$
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Influential Observations in Linear Regression
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Informa UK Limited
TWO GRAPHICAL DISPLAYS FOR OUTLYING AND INFLUENTIAL OBSERVATIONS IN REGRESSION
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Oxford University Press (OUP)
Are You Normal? The Problem of Confounded Residual Structures in Hierarchical Linear Models
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Model Choice and Diagnostics for Linear Mixed-Effects Models Using Statistics on Street Corners
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arXiv
A Statistical View of Some Chemometrics Regression Tools
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Informa UK Limited
A Genome-Wide Screen Reveals Functional Gene Clusters in the Cancer Genome and Identifies EphA2 as a Mitogen in Glioblastoma
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American Association for Cancer Research (AACR)
A Statistical View of Some Chemometrics Regression Tools
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Influential Observations in Linear Regression
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Detection of Influential Observation in Linear Regression
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A New Statistic for Influence in Linear Regression
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Random lasso
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Identifying Influential Data and Sources of Collinearity
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John Wiley & Sons, Inc.
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