【摘 要】
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We propose a novel nonparametric regression method to model the mean and covariance structures for longitudinal data, simultaneously.Like the generalized li
【机 构】
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SouthwesternUniversityofFinanceandEconomics
【出 处】
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The Third IMS-China International Conference on Statistics a
论文部分内容阅读
We propose a novel nonparametric regression method to model the mean and covariance structures for longitudinal data, simultaneously.Like the generalized linear models, the mean structure is represented by an unknown function of linear predictors.In the meantime, the within-subject covariance matrix is decomposed into a unit lower triangular matrix involving autoregressive coefficients and a diagonal matrix involving prediction errors variances, based on the modified Cholesky decomposition, in which the former is modelled by an unknown function in time lag and the latter by an unknown function in time.
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