Estimating and testing conditional sums of means in high dimensional multivariate binary data

DOI10.1016/j.jspi.2010.09.008zbMath1200.62057OpenAlexW1974530574MaRDI QIDQ607228

Junyong Park, J. Wade Davis

Publication date: 19 November 2010

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.09.008

zbMATH Keywords

empirical Bayessparsitymass spectrometryconditional MLEhigh dimensional multivariate binary data

Mathematics Subject Classification ID

Related Items (1)

False Discovery Rate Based on Extreme Values in High Dimension

Cites Work

• Estimating the mean of high valued observations in high dimensions
• High-dimensional variable selection
• Regularization through variable selection and conditional MLE with application to classification in high dimensions
• A useful empirical Bayes identity
• Estimation of sums of random variables: examples and information bounds
• Estimating a treatment effect under biased sampling.
• A class of smooth estimators for discrete distributions
• Prediction and estimation for the compound Poisson distribution
• Ideal spatial adaptation by wavelet shrinkage
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• The Empirical Bayes Approach to Statistical Decision Problems
• Testing the equality of distributions of random vectors with categorical components.

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