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Bootstrap aggregating
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51	The Newsletter of the R Project News Volume 2/3, December 2002 Add to Reading List Source URL: www.r-project.org Language: English - Date: 2015-03-04 04:31:16 Computational statistics Data analysis Econometrics Bootstrapping Resampling Breusch–Godfrey test Bootstrap aggregating Durbin–Watson statistic Non-parametric statistics Statistics Statistical inference Statistical tests
52	SM9: “Greater Urals” large-regional analysis GU1. Evaluating uncertainties in chronologies that represent different regional scales In many statistical applications, there is a balance between minimising random sampl Add to Reading List Source URL: www.cru.uea.ac.uk Language: English - Date: 2013-04-09 09:56:16 Computational statistics Measurement Dendrology Bootstrapping Dendrochronology Bootstrap aggregating Standard error Confidence interval Random sample Statistics Statistical inference Data analysis
53	Package ‘ipred’ July 2, 2014 Title Improved Predictors Version[removed]Date[removed]Description Improved predictive models by indirect classification and Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 12:12:12 Computational statistics Statistical inference Decision trees Bootstrap aggregating Random forest Bootstrapping Leo Breiman Resampling Cross-validation Statistics Machine learning Ensemble learning
54	S E D A P A PROGRAM FOR RESEARCH ON SOCIAL AND ECONOMIC DIMENSIONS OF AN AGING POPULATION Add to Reading List Source URL: socserv.mcmaster.ca Language: English - Date: 2007-03-07 10:46:30 Science Employment Bootstrapping Bootstrap aggregating Information Statistics Computational statistics
55	Finite Mixture Model Diagnostics Using Resampling Methods Bettina Gru ¨n Friedrich Leisch Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2015-02-19 17:50:14 Econometrics Regression analysis Non-parametric statistics Bootstrapping Resampling Mixture distribution Mixture model Linear regression Bootstrap aggregating Statistics Statistical inference Computational statistics
56	Package ‘polywog’ July 2, 2014 Title Bootstrapped Basis Regression with Oracle Model Selection Version[removed]Date[removed]Author Brenton Kenkel and Curtis S. Signorino Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 16:05:49 Econometrics Bootstrapping Data analysis Resampling Matrix Bootstrap aggregating Conceptual model Polynomial Model selection Statistics Computational statistics Statistical inference
57	A comparison of bootstrap methods and an adjusted bootstrap approach for estimating prediction error in microarray classification Short title: Bootstrap Prediction Error Estimation Wenyu Jiang* and Richard Simon Add to Reading List Source URL: linus.nci.nih.gov Language: English - Date: 2013-03-12 10:01:33 Computational statistics Resampling Bootstrapping Cross-validation Variance Sample size determination Bootstrap aggregating Statistics Statistical inference Data analysis
58	New URL: http://www.R-project.org/conferences/DSC[removed]Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC[removed]March 20–22, Vienna, Austria ISSN 1609-395X Add to Reading List Source URL: www.r-project.org Language: English - Date: 2014-02-10 04:17:14 Machine learning Computational statistics Regression analysis Bootstrap aggregating Random forest Linear discriminant analysis Leo Breiman Cross-validation Bootstrapping Statistics Statistical classification Ensemble learning
59	Measuring Confidence Intervals in Link Discovery: A Bootstrap Approach Jafar Adibi, Paul R. Cohen and Clayton T. Morrison Center for Research on Unexpected Events (CRUE) USC Information Sciences Institute 4676 Admiralty Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2004-08-04 04:00:19 Statistical theory Data analysis Resampling Bootstrapping Bootstrap aggregating Confidence interval Cross-validation Sampling distribution Maximum likelihood Statistics Statistical inference Computational statistics
60	Package ‘bootfs’ July 2, 2014 Type Package Title Use multiple feature selection algorithms to derive robust feature sets for two or multiclass classification problems. Version 1.4.2 Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 11:23:14 Computational statistics Ensemble learning Data analysis Resampling Null Bootstrapping Statistical hypothesis testing Support vector machine Bootstrap aggregating Statistics Information Statistical inference

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