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	Prediction of growth: A hierarchical Bayesian approach
	Arjas, E ; Liu, LP ; Maglaperidze, N
	1997
关键词	growth curve hierarchical modelling predictive distribution Bayesian credible interval GIBBS SAMPLER CURVE MODEL COMPUTATION
英文摘要	A nonparametric hierarchical growth curve, model is proposed. Different levels in the model hierarchy are intended to correspond to different sources of variation in an individual's growth. The nonparametric character of the model offers considerable flexibility in fitting the growth curves to empirical data. Here the emphasis is on prediction, and for this purpose the adopted Bayesian inferential approach seems particularly natural and efficient. A Markov chain Carlo method is used to perform the numerical computations. As an illustration of the techniques, we consider the: growth of children, during their first two years.; Mathematical & Computational Biology; Statistics & Probability; SCI(E); 2; ARTICLE; 6; 741-759; 39
语种	英语
出处	SCI
出版者	biometrical journal
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/219540]
专题	数学科学学院
推荐引用方式 GB/T 7714	Arjas, E,Liu, LP,Maglaperidze, N. Prediction of growth: A hierarchical Bayesian approach. 1997-01-01.

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