Interacting cluster point process model for epidermal nerve fibers

Autor(es)

Garcia, Nancy L. ^[1] ; Guttorp, Peter ^[2] ; Ludwig, Guilherme ^[1]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Campinas, SP - Brazil

^[2] Norwegian Comp Ctr, Oslo - Norway

• Tipo de documento: Artigo Científico
• Fonte: SPATIAL STATISTICS; v. 35, MAR 2020.
• Citações Web of Science: 0

Resumo

We propose an interacting cluster model for the spatial distribution of epidermal nerve fibers (ENF). The model consists of a spatial process of parent points modeling the base points of nerve fiber bundles. To each base point there is an offspring point process of fibers end points associated. The parent process is, possibly, inhibited by fiber endings that belong to different base bundles. The fibers themselves have random length and spatial orientation. We consider a non-orphan process where we can connect each offspring to a parent. We examine the processes that can be described with our model, how coefficient estimation can be performed under the Bayesian paradigm via Markov chain Monte Carlo methods, and detail approaches for the implementation of efficient MCMC sampling schemes. We study the performance of the estimation procedure through a simulation study. An application to data from skin blister biopsy images of ENFs is presented. (C) 2020 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 14/26419-0 - Análise de dados espaço-temporais agregados
• Beneficiário: Nancy Lopes Garcia
• Modalidade de apoio: Bolsas no Exterior - Pesquisa
• Processo FAPESP: 16/09390-4 - Inferência para processos pontuais não-Poissonianos
• Beneficiário: Guilherme Vieira Nunes Ludwig
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 18/09877-6 - 2018 Joint Statistical Meetings
• Beneficiário: Guilherme Vieira Nunes Ludwig
• Modalidade de apoio: Auxílio à Pesquisa - Reunião - Exterior
• Processo FAPESP: 17/15306-9 - Incorporando Covariaveis Functionais em Modelos de Regressão Não Paramétricos
• Beneficiário: Nancy Lopes Garcia
• Modalidade de apoio: Auxílio à Pesquisa - Regular