Clustering regions with dynamic time warping to model obesity prevalence disparities in the United States
DOI10.1080/02664763.2023.2192445MaRDI QIDQ6547188
[[Person:6547185|Author name not available (Why is that?)]], [[Person:6547187|Author name not available (Why is that?)]], Tatjana Miljkovic, [[Person:6547186|Author name not available (Why is that?)]]
Publication date: 30 May 2024
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric inference (62G99)
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- A global averaging method for dynamic time warping, with applications to clustering
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- Predictive Modeling of Obesity Prevalence for the U.S. Population
- Identifying subgroups of age and cohort effects in obesity prevalence
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