Jeffrey S. Morris

The University of Texas MD Anderson Cancer Center

Associate Professor, Department of Biostatistics
Contact Information
Curriculum Vitae [PDF]

Expertise

Functional Data Analysis, Genomics, Proteomics, Bayesian Methods, Wavelets

Honors & Awards

ASA Noether Young Scholar Award, 2005
Thomson-ESI Hot Paper in the Field of Computer Science, July 2005
The University of Texas M. D. Anderson Cancer Center E.N. Cobb Faculty Scholar Award, 2004
Best Presentation, 4th Critical Assessment of Microarray Data Analysis (CAMDA), 2003
ISBA Mitchell Prize for Outstanding Bayesian Application Paper, 2003
JASA Applications and Case Studies Edtior's Invited Paper, 2003
Travel Award, Biometrics Section of ASA, 2001

Links

The BLUPs Are Not “Best” When It Comes To Bootstrapping

Jeffrey S. Morris, The University of Texas M.D. Anderson Cancer Center

Abstract

In the setting of mixed models, some researchers may construct a semiparametric bootstrap by sampling from the best linear unbiased predictor residuals. This paper demonstrates both mathematically and by simulation that such a bootstrap will consistently underestimate the variation in the data in finite samples.

Suggested Citation

Jeffrey S. Morris. " The BLUPs Are Not “Best” When It Comes To Bootstrapping" Statistics and Probability Letters 56 (2002): 425-430.
Available at: http://works.bepress.com/jeffrey_s_morris/30

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Selected Works of Jeffrey S. Morris