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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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MATS: Inference for potentially Singular and Heteroscedastic MANOVA [PDF]
, 2017 In many experiments in the life sciences, several endpoints are recorded per subject. The analysis of such multivariate data is usually based on MANOVA models assuming multivariate normality and covariance homogeneity.
Friedrich, Sarah, Pauly, Markus
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Robust estimation of risks from small samples [PDF]
, 2017 Data-driven risk analysis involves the inference of probability distributions from measured or simulated data. In the case of a highly reliable system, such as the electricity grid, the amount of relevant data is often exceedingly limited, but the impact
Strbac, Goran, Tindemans, Simon H.
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Consistent tests of conditional moment restrictions [PDF]
, 2006 We propose two classes of consistent tests in parametric econometric models defined through multiple conditional moment restrictions. The first type of tests relies on nonparametric estimation, while the second relies on a functional of a marked ...
Delgado, Miguel A. +2 more
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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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Bootstraping financial time series [PDF]
, 2002 It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations ...
Pascual, Lorenzo, Ruiz Ortega, Esther
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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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