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Collaborative Research: Resampling bridges for complex data — NSF Award to University of Rhode Island (RI, $99,924)

This research aims to produce efficient and accurate statistical methodology that can be applied in practice without strong assumptions about data. In many industrial and scientific applications, current statistical analyses often require an adequate model for data, which can often be uncertain and practically difficul

Award titleCollaborative Research: Resampling bridges for complex data
Award ID2515718
AwardeeUniversity of Rhode Island
CityKINGSTON
StateRI
Amount obligated$99,924
Principal investigatorHaihan Yu
ProgramSTATISTICS, OFFICE OF MULTIDISCIPLINARY AC
Start date08/01/2025
AbstractThis research aims to produce efficient and accurate statistical methodology that can be applied in practice without strong assumptions about data. In many industrial and scientific applications, current statistical analyses often require an adequate model for data, which can often be uncertain and practically difficult to choose. This situation can be problematic, though, because any conclusions drawn from a mistaken model may be unreliable or misleading. As a remedy, a direct benefit of this p
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