![]() Proposed sequences of simultaneous confidence sets generalize the idea of repeated confidence intervals to the case of multiple parameters and achieve the desired overall confidence level. The new methodology combines flexibility and cost-optimization of sequential procedures with the ability of modern statistical methods for multiple comparisons to control the familywise error rate and power. It searches for optimal stopping rules that minimize the expected cost of the experiment while controlling for the false positive and false negative rates. This study extends the recently obtained step-up and step-down procedures for multiple comparisons to sequential designs. ![]() This includes testing multiple hypotheses, constructing sequences of simultaneous confidence sets, detecting changes in multiple channels, and making other sequential statistical decisions involving multiple parameters or multiple measurements. It aims to develop cost-minimizing methods and supporting theory for conducting multiple statistical inferences sequentially. The project focuses on the development of new theory and methodology of sequential multiple comparisons. Primary Place of Performance Congressional District:Ġ40100 NSF RESEARCH & RELATED ACTIVIT 040100 NSF RESEARCH & RELATED ACTIVIT 040100 NSF RESEARCH & RELATED ACTIVIT Michael Baron (Principal Investigator) Sponsored Research Office:.Gabor Szekely DMS Division Of Mathematical Sciences MPS Direct For Mathematical & Physical ScienįY 2010 = $75,565.00 FY 2011 = $72,562.00 FY 2012 = $51,873.00 Sequential testing of multiple hypotheses, simultaneous confidence estimation, and multichannel change-point detection NSF Org:
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