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Activity Number:
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452
- Advancements in Complex Functional Data Analysis
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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Abstract #326492
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Title:
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Boosting Functional Response Models for Location, Scale, and Shape with an Application to Bacterial Competition
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Author(s):
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Almond Stöcker and Sarah Brockhaus and Sophia Schaffer and Benedikt von Bronk and Madeleine Opitz and Sonja Greven*
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Companies:
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LMU Munich and LMU Munich and LMU Munich and LMU Munich and LMU Munich and LMU Munich
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Keywords:
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functional data;
functional regression;
GAMLSS;
Generalized Additive Models for Location, Scale, and Shape
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Abstract:
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We extend Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to regression with functional response. GAMLSS are a flexible model class allowing for modeling multiple distributional parameters at once. The model is fitted via gradient boosting, which provides inherent model selection. We apply the functional GAMLSS to analyze bacterial interaction in Escherichia coli and show how the consideration of variance structure fruitfully extends usual growth models.
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Authors who are presenting talks have a * after their name.
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