Approximate maximum likelihood estimation of the autologistic model

DOI10.1016/j.csda.2014.10.019OpenAlexW2067441297MaRDI QIDQ1623803

Giuseppe Espa, Diego Giuliani, Marco Bee

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://www.unitn.it/files/download/27419/demdp2013_12.pdf

zbMATH Keywords

sufficient statisticsspatial modelskernel densityneighborhood relation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Computational methods for problems pertaining to statistics (62-08) Inference from spatial processes (62M30) Random fields; image analysis (62M40)

Related Items (4)

Approximate maximum likelihood estimation of the Bingham distribution ⋮ Some analytical results on bivariate stable distributions with an application in operational risk ⋮ Unsupervised mixture estimation via approximate maximum likelihood based on the Cramér-von Mises distance ⋮ A characteristic function-based approach to approximate maximum likelihood estimation

Uses Software

• R
• ks
• agridat
• ssfit
• DALL
• bootlib

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Data. A collection of problems from many fields for the student and research worker
• On consistency of a class of estimators for exponential families of Markov random fields on the lattice
• Generalized pseudo-likelihood estimates for Markov random fields on lattice
• Analysis of dependent competing risks in the presence of progressive hybrid censoring using Marshall-Olkin bivariate Weibull distribution
• A simple approach to maximum intractable likelihood estimation
• Multivariate plug-in bandwidth selection
• Spatial econometrics. Statistical foundations and applications to regional convergence.
• Maximum Likelihood Estimation for Spatial Models by Markov Chain Monte Carlo Stochastic Approximation
• The fitting of complex parametric models
• Exploring Dependence with Data on Spatial Lattices
• Markov Chain Monte Carlo for Autologistic Regression Models with Application to the Distribution of Plant Species
• Density Estimation for the Metropolis–Hastings Algorithm
• Exact sampling with coupled Markov chains and applications to statistical mechanics
• Equation of State Calculations by Fast Computing Machines
• ABC likelihood-free methods for model choice in Gibbs random fields

This page was built for publication: Approximate maximum likelihood estimation of the autologistic model