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Bayesian spatial transformation models with applications in neuroimaging data

The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with...

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Bibliografski detalji
Glavni autori: Miranda, Michelle F., Zhu, Hongtu, Ibrahim, Joseph G.
Format: Artigo
Jezik:Inglês
Izdano: 2013
Teme:
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC3864982/
https://ncbi.nlm.nih.gov/pubmed/24128143
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12085
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