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UID:calendar.444221.field_event_date.0@www.wright.edu
DTSTAMP:20260219T180528Z
CREATED:20220329T134929Z
DESCRIPTION:In modern high-throughput plant phenotyping\, images of plants 
 of different genotypes are repeatedly taken throughout the growing season\
 , and phenotypic traits of plants (e.g.\, plant height) are extracted thro
 ugh image processing. It is of interest to recover whole trait trajectorie
 s and their derivatives at both genotype and plant levels based on observa
 tions made at irregular discrete time points. We propose to model trait tr
 ajectories using hierarchical functional principal component analysis (HFP
 CA) and show that the problem of recovering derivatives of the trajectorie
 s is reduced to estimating derivatives of eigenfunctions\, which is solved
  by differentiating eigenequations. Simulation studies show that the propo
 sed procedure performs better than its competitors in terms of recovering 
 both trait trajectories and their derivatives. Interesting characteristics
  of plant growth dynamics are revealed in the application to a modern plan
 t phenotyping study.Speaker Bio: Yuhang Xu is an assistant professor in st
 atistics in the Department of Applied Statistics and Operations Research a
 t Bowling Green State University. He received his Ph.D. in Statistics from
  Iowa State University in 2016. After graduation\, he worked as an assista
 nt professor in the Department of Statistics at the University of Nebraska
 -Lincoln from 2016 to 2019. His research interests include functional data
  analysis\, survival analysis\, measurement error\, and interdisciplinary 
 research in business\, plant science\, chemistry\, etc.Event Webpage: http
 s://wright.webex.com/wright/j.php?MTID=mf8164b12edfa010c874e0ffaa514b66c
DTSTART;TZID=America/New_York:20220401T143000
DTEND;TZID=America/New_York:20220401T170000
LAST-MODIFIED:20220329T171450Z
LOCATION:Virtual
SUMMARY:Growth dynamics for plant high-throughput phenotyping studies using
  hierarchical functional data analysis
URL;TYPE=URI:/events/growth-dynamics-plant-high-throu
 ghput-phenotyping-studies-using-hierarchical-functional-data
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