TY - JOUR
T1 - Estimating the mean of high valued observations in high dimensions
AU - Greenshtein, Eitan
AU - Park, Junyong
AU - Ritov, Ya’Acov
PY - 2008
Y1 - 2008
N2 - Let Yi ~ N(μi,1), i = 1,…, n, be independent random variables. We study the problem of estimating the quantity S = Σ{i|Ci}μi. We emphasize the case where n is large, the vector (μ1,…,μn) is sparse, and the value of C is large. Our approach is nonparametric empirical Bayes, where μi are assumed i.i.d from an unknown G. The performance of our suggested estimator is studied both theoretically and through simulations. We also obtain some results related to the local false discovery rates corresponding to high valued points Yi.
AB - Let Yi ~ N(μi,1), i = 1,…, n, be independent random variables. We study the problem of estimating the quantity S = Σ{i|Ci}μi. We emphasize the case where n is large, the vector (μ1,…,μn) is sparse, and the value of C is large. Our approach is nonparametric empirical Bayes, where μi are assumed i.i.d from an unknown G. The performance of our suggested estimator is studied both theoretically and through simulations. We also obtain some results related to the local false discovery rates corresponding to high valued points Yi.
KW - Empirical Bayes
KW - FDR
KW - Sparse vector
UR - http://www.scopus.com/inward/record.url?scp=85008827350&partnerID=8YFLogxK
U2 - 10.1080/15598608.2008.10411883
DO - 10.1080/15598608.2008.10411883
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AN - SCOPUS:85008827350
SN - 1559-8608
VL - 2
SP - 408
EP - 418
JO - Journal of Statistical Theory and Practice
JF - Journal of Statistical Theory and Practice
IS - 3
ER -