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A method of predicting the number of clusters using Rand's statistic
Affiliation:1. Department of Applied Statistics, Daejeon University, Daejeon 300-716, Republic of Korea;2. Department of Mathematics and Statistics, Mississippi State University, Starkville, MS 39762, USA;3. Department of Statistics, Oklahoma State University, Stillwater, OK 74078, USA;1. University of Navarra, Department of Preventive Medicine and Public Health, School of Medicine, Pamplona, Spain;2. CIBER Pathophysiology of Obesity and Nutrition (CIBERobn), Institute of Health Carlos III, Madrid, Spain;3. IDISNA Navarra’s Health Research Institute, Pamplona, Spain;4. Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States;5. Nutrition Research group, Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Spain;6. Department of Psychiatry and Medical Psychology, University Clinic of Navarra, Spain;1. Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA;2. Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA;3. Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA;4. Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA;5. Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA;1. Hubei Key Lab. for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430079, Hubei, China;2. Department of Geography and Planning, Queen’s University, Kingston, Ontario K7L 3N6, Canada;3. Hubei Provincial Development and Reform Commission/Central China Normal University, Research Institute of Two-Oriented Society Construction in Wuhan Urban Agglomeration, Wuhan 430079, Hubei, China
Abstract:
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