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偏斜纵向数据的偏正态前依赖模型AI 解读

Antedependence models, also known as transition models, have proven to be useful for longitudinal data exhibiting serial correlation, especially when the variances and/or same-lag correlations are time-varying. Statistical inference procedures associated with normal antedependence models are well-developed and have many nice properties, but they are not appropriate for longitudinal data that exhibit considerable skewness. We propose two direct extensions of normal…

空间统计中两种渐近框架的协调AI 解读

Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have been advanced for obtaining limiting distributions of maximum likelihood estimators of covariance parameters in Gaussian spatial models with or without a nugget effect. These limiting distributions are known to be different in some cases. It is therefore of interest to know, for a given finite sample, which framework is more appropriate. We consider the possibility of making this choice on…

田间小区试验中 Papadakis 及其他非线性处理对比估计量的无偏性AI 解读

Spatial methods for the analysis of field-plot experiments are considered. Estimators of treatment contrasts obtained by these methods are generally complicated nonlinear functions of the observations. Sufficient conditions for these estimators to be unbiased under a postulated true model are obtained.

田间小区实验中 Papadakis 及其他非线性处理对比估计量的无偏性AI 解读

Spatial methods for the analysis of field-plot experiments are considered. Estimators of treatment contrasts obtained by these methods are generally complicated nonlinear functions of the observations. Sufficient conditions for these estimators to be unbiased under a postulated true model are obtained.