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Activity Number:
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216
- Recent Advances in Nonparametric and Semiparametric Methods for Complex Data
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Type:
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Invited
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Date/Time:
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Tuesday, August 9, 2022 : 8:30 AM to 10:20 AM
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Sponsor:
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Journal of Nonparametric Statistics
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Abstract #320625
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Title:
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Estimating the Distribution of Episodically Consumed Foods Measured with Error
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Author(s):
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Aurore Delaigle* and Felix Camirand Lemyre and Raymond J. Carroll
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Companies:
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University of Melbourne and University of Sherbrooke and Texas A&M University
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Keywords:
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deconvolution;
noisy data;
classical measurement errors;
kernel estimator;
errors-in-variables;
nutrition
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Abstract:
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Dietary data collected from 24-hour dietary recalls are observed with significant measurement errors. In the nonparametric curve estimation literature, a lot of effort has been devoted to designing methods that are consistent under contamination by noise. However, some foods such as alcohol or fruits are consumed only episodically, and may not be consumed during the day when the 24-hour recall is administered. Existing nonparametric methods cannot deal with those so-called excess zeros. We present new estimators of the distribution of such episodically consumed food data measured with errors.
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Authors who are presenting talks have a * after their name.
