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Resampling Plans and the Estimation of Prediction Error
Stats, 2021 This article was prepared for the Special Issue on Resampling methods for statistical inference of the 2020s. Modern algorithms such as random forests and deep learning are automatic machines for producing prediction rules from training data.
Bradley Efron
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A new distribution-free approach to constructing the confidence region for multiple parameters. [PDF]
PLoS ONE, 2013 Construction of confidence intervals or regions is an important part of statistical inference. The usual approach to constructing a confidence interval for a single parameter or confidence region for two or more parameters requires that the distribution ...
Zhiqiu Hu, Rong-Cai Yang
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An integrated approach for the analysis of biological pathways using mixed models. [PDF]
PLoS Genetics, 2008 Gene class, ontology, or pathway testing analysis has become increasingly popular in microarray data analysis. Such approaches allow the integration of gene annotation databases, such as Gene Ontology and KEGG Pathway, to formally test for subtle but ...
Lily Wang +3 more
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Effects of dating errors on nonparametric trend analyses of speleothem time series [PDF]
Climate of the Past, 2012 A fundamental problem in paleoclimatology is to take fully into account the various error sources when examining proxy records with quantitative methods of statistical time series analysis.
M. Mudelsee, J. Fohlmeister, D. Scholz
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Journal of Statistical Software, 2013 We introduce and examine dbEmpLikeGOF, an R package for performing goodness-of-fit tests based on sample entropy. This package also performs the two sample distribution comparison test.
Jeffrey Miecznikowski +2 more
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Nonparametric Statistical Thresholding for Sparse Magnetoencephalography Source Reconstructions
Frontiers in Neuroscience, 2012 Uncovering brain activity from MEG data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources.
Julia Parsons Owen +4 more
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BMC Evolutionary Biology, 2005 Background For parsimony analyses, the most common way to estimate confidence is by resampling plans (nonparametric bootstrap, jackknife), and Bremer support (Decay indices).
Müller Kai F
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Mapping topographic structure in white matter pathways with level set trees.
PLoS ONE, 2014 Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees-
Brian P Kent +3 more
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Permutation-Based Analysis of Clinical Variables in Necrotizing Fasciitis Using NPC and Bootstrap
MathematicsNecrotizing fasciitis (NF) is a rare but aggressive soft tissue infection with high rates of mortality and amputation, making early identification of key prognostic biomarkers essential for clinical management. However, the rarity and heterogeneity of NF
Gianfranco Piscopo +3 more
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Nonparametric Bootstrap Likelihood Estimation to Investigate the Chance Set-Up on Clustering Results
IEEE Open Journal of the Computer SocietyClustering algorithms are widely used in the knowledge discovery domain, but concerns and questions about the validity of the results must be considered.
Ammar Elnour, Wencheng Yang, Yan Li
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