今天是2024年12月15日 星期日 kmmc 退出

Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology

http://www.firstlight.cn2009/9/24

[作者] Chunlin Ji Daniel Merl Thomas B. Kepler Mike West

[单位] Department of Statistical Science, Duke University, Durham, NC , mailto Department of Immunology, Duke University Medical Center

[摘要] We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point process that p…

[关键词] Bayesian computation blocked Gibbs sampler Dirichlet process mixture model inhomogeneous Poisson process

We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point process that provide indirect and noisy data on locations of point outcomes. We are interested in problems in which the spatial intensity function may be highly heterogenous, and so is modelled via flexiblenonparametric Bayesian mixture models. Analysis aims to estimate the underlying intensity function and the abundance of realized but unobserved points. Our motivating applications involve immunological studies of multiple fluorescent intensity images in sections of lymphatic tissue where the point processes represent geographical configurations of cells. We are interested in estimating intensity functions and cell abundance for each of a series of such data sets to facilitate comparisons of outcomes at different times and with respect to differing experimental conditions. The analysis is heavily computational, utilizing recently introduced MCMC approaches for spatial point process mixtures and extending them to the broader new context here of unobserved outcomes. Further, our example applications are problems in which the individual objects of interest are not simply points, but rather small groups of pixels; this implies a need to work at an aggregate pixel region level and we develop the resulting novel methodology for this. Two examples with with immunofluorescence histology data demonstrate the models and computational methodology.

存档附件原文地址

原文发布时间:2009/9/24

引用本文:

Chunlin Ji;Daniel Merl;Thomas B. Kepler;Mike West.Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histologyhttp://kmmc.firstlight.cn/View.aspx?infoid=807707&cb=wangzhijuanxg
发布时间:2009/9/24.检索时间:2024/12/15

中国研究生教育排行榜-

正在加载...

中国学术期刊排行榜-

正在加载...

世界大学科研机构排行榜-

正在加载...

中国大学排行榜-

正在加载...

人 物-

正在加载...

课 件-

正在加载...

视听资料-

正在加载...

研招资料 -

正在加载...

知识要闻-

正在加载...

国际动态-

正在加载...

会议中心-

正在加载...

学术指南-

正在加载...

学术站点-

正在加载...