Mixed models for the analysis of replicated spatial point patterns
Mixed models for the analysis of replicated spatial point patterns
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DOI：
10.1093/biostatistics/kxh014
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发表时间：
2004-10-01
期刊：
影响因子：
2.1
通讯作者：
Grunwald, GK
中科院分区：
文献类型：
--
作者：
Bell, ML;Grunwald, GK
在复杂的设计，如那些包括复制的空间点模式的分析的统计方法是相当不发达。通过扩展Baddeley和Turner（2000，Australian and New Zealand Journal of Statistics 42，283-322）关于单一模式的伪像的工作，结合最大伪像和广义线性混合建模来开发混合模型。对参数估计进行了仿真实验。固定和混合效应模型进行了比较，并在某些方面的混合模型被发现是上级。显示了使用施特劳斯过程对死后脑切片中的神经元位置进行建模的示例。
The statistical methodology for the analysis of replicated spatial point patterns in complex designs such as those including replications is fairly undeveloped. A mixed model is developed in conjunction with maximum pseudolikelihood and generalized linear mixed modeling by extending Baddeley and Turner's (2000, Australian and New Zealand Journal of Statistics 42, 283-322) work on pseudolikelihood for single patterns. A simulation experiment is performed on parameter estimation. Fixed- and mixed-effect models are compared, and in some respects the mixed model is found to be superior. An example using the Strauss process for modeling neuron locations in post-mortem brain slices is shown.