Optimal designs in growth curve models: Part I Correlated model for linear growth: Optimal designs for slope parameter estimation and growth prediction |
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| Institution: | 1. Institut für Mathematik, Universität Augsburg, Germany;2. Statistics Unit, Department of Mathematical Sciences, University of Tampere, Finland;3. Department of Statistics, Calcutta University, India;1. Departamento de Fisiología Vegetal, Facultad de Ciencias, Universidad de Granada, Campus de Fuentenueva s/n, Granada, Spain;2. Plant Cell Biotechnology Lab, Instituto de Tecnologia Química e Biológica António Xavier (Green-it Unit), Universidade Nova de Lisboa, Oeiras, Portugal;3. Departamento Biologia Vegetal, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Portugal;1. Department of Orthopedics, Second Affiliated Hospital of Xi''an Jiaotong University, Xi''an, Shaanxi Province, China;2. Department of Orthopedics, Shenzhen University General Hospital, Shenzhen, Guangdong Province, China;1. Department of Biology, National and Kapodistrian University of Athens, Panepistimioupolis 15784, Athens, Greece;1. Department of Genetics and Biotechnology, St. Petersburg State University, 199034, St. Petersburg, Russia;2. All-Russia Research Institute for Agricultural Microbiology, 196608, St. Petersburg, Russia |
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| Abstract: | In the present paper we discuss the situation for a linear growth with correlated structure of the errors and indicate the nature of optimal designs for estimation and prediction problems. We study the intraclass structure of the error distribution. As regards estimation of the slope parameter, we look for robust optimal designs. Here robustness means that optimality should hold for a large variety of correlation parameters. The robust optimal designs for the prediction problem center around a performance measure of the predictors for all design points simultaneously. We have also studied the autocorrelated error structure and found similar results which are reported very briefly. |
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