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In the absence of relevant prior experience, popular Bayesian estimation techniques usually
begin with some form of \uninformative" prior distribution intended to have minimal inferential
in
uence....
Estimation and Accuracy after Model Selection
model averaging Cp, Lasso bagging bootstrap smoothing
2015/8/20
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consider
bootstrap methods for computing standard errors and con dence intervals that take model selecti...
Improving accuracy and power with transfer learning using a meta-analytic database
Meta-analysis,fMRI,multiple comparison,machine learning
2012/11/23
Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on an...