Hierarchical testing of variable importance

Keywords

Variable (mathematics), Mathematics, Statistics, Library science, Computer science

References

• Some Comments on CpCohn L. Mallows — 2000
• THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCYYoav Benjamini, Daniel Yekutieli — 2001
• Supervised harvesting of expression treesTrevor Hastie, Robert Tibshirani, David Botstein — 2001
• Asymptotics for lasso-type estimatorsWenjiang Fu, Keith Knight — 2000
• Higher criticism for detecting sparse heterogeneous mixturesDavid L. Donoho, Jiashun Jin — 2004
• Addendum: Regularization and variable selection via the elastic netHui Zou, Trevor Hastie — 2005
• How Many Variables Should Be Entered in a Regression EquationLeo Breiman, Darcy A. Freedman — 1983
• High-dimensional graphs and variable selection with the LassoNicolai Meinshausen, Peter Bühlmann — 2006
• Hierarchical Grouping to Optimize an Objective FunctionJoe H. Ward — 1963
• The Adaptive Lasso and Its Oracle PropertiesHui Zou — 2006
• Modified Sequentially Rejective Multiple Test ProceduresJuliet Popper Shaffer — 1986
• Testing against a high dimensional alternativeJelle J. Goeman, Sara A. van de Geer, Hans C. van Houwelingen — 2006
• False Discovery Control for Multiple Tests of Association Under General DependenceNicolai Meinshausen — 2006
• Better subset regression using the nonnegative garroteLeo Breiman — 1995
• False Discovery Control for Random FieldsMarco Perone Pacifico, Christopher R. Genovese, Isabella Verdinelli — 2004
• More comments on C pColin L. Mallows — 1995
• A Statistical View of Some Chemometrics Regression Toolslldiko E. Frank, Jerome H. Friedman — 1993
• Gene Ontology: tool for the unification of biologyMichael Ashburner, Catherine A. Ball, Judith A. Blake — 2000
• The group lasso for logistic regressionLukas Meier, Sara van de Geer, Peter Bühlmann — 2008
• Controlling the false discovery rate: a practical and powerful approach to multiple testingYoav Benjamini, Yosef Hochberg — 1995

Cited by

• Computational ortholog prediction: evaluating use cases and improving high-throughput performanceMatthew D. Whiteside — 2013
• Integrated Testing Strategy (ITS) - Opportunities to better use existing data and guide future testing in toxicology.Joanna Jaworska — 2010
• A tutorial on the inheritance procedure for multiple testing of tree-structured hypothesesDilinuer Kuerban — 2013
• Statistical Significance for Hierarchical ClusteringPatrick K. Kimes, Yufeng Liu, D. Neil Hayes — 2014
• A Picture is Worth a Thousand TablesAndreas Krause, Michael O’Connell — 2012
• A Hidden Markov Model Approach to Testing Multiple Hypotheses on a Gene Ontology GraphKun Liang, Dan Nettleton — 2009
• Exact Multivariate Tests - A New Effective Principle of Controlled Model ChoiceJuergen Laeuter, Maciej Rosołowski, Ekkehard Glimm — 2012
• Locally epistatic genomic relationship matrices for genomic association, prediction and selectionDeniz Akdemir — 2013
• Global tests of association for multivariate ordinal dataMonika Jelizarow — 2015
• Scalar-Invariant Test for High-Dimensional Regression CoefficientsLong Feng — 2015
• A multiple testing method for hypotheses structured in a directed acyclic graphRosa J. Meijer, Jelle J. Goeman — 2015
• Hidden Markov models for simultaneous testing of multiple gene sets and adaptive and dynamic adaptive procedures for false discovery rate control and estimationKun Liang — 2010
• Performance of a blockwise approach in variable selection using linkage disequilibrium informationAlia Dehman, Christophe Ambroise, Pierre Neuvial — 2015
• Discovering the false discovery rateYoav Benjamini — 2010
• Association Between a Prognostic Gene Signature and Functional Gene SetsManuela Hummel, Klaus H. Metzeler, Christian Buske — 2008
• A Cochran–Armitage‐type and a score‐free global test for multivariate ordinal dataMonika Jelizarow, Ulrich Mansmann, Jelle J. Goeman — 2016
• High-Dimensional Inference: Confidence Intervals, p-Values and R-Software hdiRuben Dezeure, Peter Bühlmann, Lukas Meier — 2014
• Strategien für die Expressionsanalyse in funktionellen GengruppenManuela Hummel — 2009
• Sensitivity Analysis for Multiple Comparisons in Matched Observational Studies Through Quadratically Constrained Linear ProgrammingColin B. Fogarty, Dylan S. Small — 2015
• Genomic Prediction of Quantitative Traits using Sparse and Locally Epistatic ModelsDeniz Akdemir — 2014

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