Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes

Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although the maximum composite likelihood estimator has frequentist properties akin to those of the usual maximum likelihood estimator, Bayesian inference based on composite likelihoods has yet to be explored. In this paper we investigate the use of the Metropolis--Hastings algorithm to compute a pseudo-posterior distribution based on the composite likelihood. Two methodologies for adjusting the algorithm are presented and their performance on approximating the true posterior distribution is investigated using simulated data sets and real data on spatial extremes of rainfall.

• Publication year

  2009

• Venue

  arXiv: Methodology

• Publication date

  2009-11-27

• Fields of study

  Mathematics, Environmental Science

• Identifiers
  DOI 10.5705/SS.2009.248arXiv 0911.5357
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Bayesian composite marginal likelihoods

  2011influential reference
• On the likelihood function of Gaussian max-stable processes

  2011cited by this paper
• Prior Distributions From Pseudo-Likelihoods in the Presence of Nuisance Parameters

  2009cited by this paper
• Hierarchical modeling for extreme values observed over space and time

  2009cited by this paper
• Likelihood-Based Inference for Max-Stable Processes

  2009influential reference
• An extended Gaussian max-stable process model for spatial extremes

  2009cited by this paper
• Stationary max-stable fields associated to negative definite functions.

  2008cited by this paper
• On composite marginal likelihoods

  2008cited by this paper
• Inference for clustered data using the independence loglikelihood

  2007influential reference
• Bayesian Spatial Modeling of Extreme Precipitation Return Levels

  2007cited by this paper
• Probability matching property of adjusted likelihoods

  2006cited by this paper
• Spatial extremes: Models for the stationary case

  2006cited by this paper
• MAX-STABLE PROCESSES AND SPATIAL EXTREMES

  2005cited by this paper
• Monte Carlo Statistical Methods (Springer Texts in Statistics)

  2005cited by this paper
• Monte Carlo Statistical Methods

  2004influential reference
• Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics

  2004cited by this paper
• Bayesian empirical likelihood

  2003cited by this paper
• Models for Stationary Max-Stable Random Fields

  2002cited by this paper
• Computational Bayesian Analysis of Hidden Markov Models

  1998cited by this paper
• Bayes and likelihood calculations from confidence intervals

  1993cited by this paper
• Proper likelihoods for Bayesian analysis

  1992cited by this paper
• Hypothesis testing of regression parameters in semiparametric generalized linear models for cluster correlated data

  1990cited by this paper
• A Spectral Representation for Max-stable Processes

  1984cited by this paper
• Robust properties of likelihood ratio tests

  1982influential reference
• The Likelihood Surface in the Linear Functional Relationship Problem

  1972cited by this paper
• Norges Teknisk-naturvitenskapelige Universitet Fitting Gaussian Markov Random Fields to Gaussian Fields Fitting Gaussian Markov Random Fields to Gaussian Fields Tmr Project on Spatial Statistics (erb-fmrx-ct960095) for Support and Inspiration

  year unknowncited by this paper

• Differentially Private Bayesian Inference for Gaussian Copula Correlations

  2026cites this paper
• The evolving categories multinomial distribution: introduction with applications to movement ecology and vote transfer

  2025cites this paper
• Fast and Accurate Node-Age Estimation Under Fossil Calibration Uncertainty Using the Adjusted Pairwise Likelihood

  2025influential citation
• Efficient Bayesian Inference for Spatial Point Patterns Using the Palm Likelihood

  2025influential citation
• Endogenous Technology Spillovers in R&D Collaboration Networks

  2025cites this paper
• The Learning Rate Is Not a Constant: Sandwich-Adjusted Markov Chain Monte Carlo Simulation

  2025cites this paper
• An Approach to Design Adaptive Clinical Trials With Time‐to‐Event Outcomes Based on a General Bayesian Posterior Distribution

  2025cites this paper
• Representative dietary behavior patterns and associations with cardiometabolic outcomes in Puerto Rico using a Bayesian latent class analysis for non-probability samples

  2025cites this paper
• High-Dimensional Covariate-Dependent Gaussian Graphical Models

  2025cites this paper
• Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood

  2025influential citation
• Uncertainty Quantification for Multi-level Models Using the Survey-Weighted Pseudo-Posterior

  2025cites this paper
• Bayes Factor Tests for Group Differences in Ordinal and Binary Graphical Models

  2025cites this paper
• Composite Likelihood Adjustment in Bayesian Inference for Estimating Species Tree Parameters Under the Multispecies Coalescent

  2025influential citation
• A Bayesian multivariate extreme value mixture model

  2024cites this paper
• Bayesian Inference of Multiple Ising Models for Heterogeneous Public Opinion Survey Networks

  2024cites this paper
• Spatial Extremal Modelling: A Case Study on the Interplay Between Margins and Dependence

  2024cites this paper
• Exploiting multivariate network meta-analysis: A calibrated Bayesian composite likelihood inference

  2024influential citation
• Bayesian composite confidence interval for the tail index under randomly right-censored data

  2024cites this paper
• Approximate Bayesian Computation with Deep Learning and Conformal prediction

  2024cites this paper
• Accelerated Bayesian inference of population size history from recombining sequence data

  2024cites this paper
• Bayesian Model Selection via Composite Likelihood for High‐dimensional Data Integration

  2024cites this paper
• Changes in the distribution of annual maximum temperatures in Europe

  2023cites this paper
• Distributed Bayesian Inference in Massive Spatial Data

  2023cites this paper
• On the Stability of General Bayesian Inference

  2023cites this paper
• Bayesian inference for generalized linear models via quasi-posteriors.

  2023cites this paper
• Pseudo-Bayesian unit level modeling for small area estimation under informative sampling

  2023cites this paper
• Smooth copula‐based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada

  2023cites this paper
• csSampling: An R Package for Bayesian Models for Complex Survey Data

  2023cites this paper
• Fast spatial simulation of extreme high-resolution radar precipitation data using INLA

  2023cites this paper
• Spatial Modeling of Extremes and an Angular Component

  2023cites this paper
• A general Bayesian approach to design adaptive clinical trials with time-to-event outcomes

  2023cites this paper
• Bernstein - von Mises theorem and misspecified models: a review

  2022cites this paper
• An efficient workflow for modelling high-dimensional spatial extremes

  2022influential citation
• Adjusting Posteriors from Composite and Misspecified Likelihoods with Application to Spatial Extremes in R-INLA

  2022influential citation
• Modeling extremal streamflow using deep learning approximations and a flexible spatial process

  2022cites this paper
• Implications of modeling seasonal differences in the extremal dependence of rainfall maxima

  2022cites this paper
• COMPOSITE MIXTURE OF LOG-LINEAR MODELS WITH APPLICATION TO PSYCHIATRIC STUDIES.

  2022cites this paper
• An Effective Trend Surface Fitting Framework for Spatial Analysis of Extreme Events

  2022cites this paper
• Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations

  2022influential citation
• In the psychological literature, the investigation of the relationship between psychoses

  2021cites this paper
• Hierarchical Bayesian Model for Assessing Extreme Daily Rainfall Through Combining Climatic and Topographic Information

  2021cites this paper
• Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data

  2021cites this paper
• A flexible Bayesian hierarchical modeling framework for spatially dependent peaks-over-threshold data

  2021cites this paper
• Neural networks for parameter estimation in intractable models

  2021cites this paper
• General Bayesian loss function selection and the use of improper models

  2021influential citation
• A Hidden Climate Indices Modeling Framework for Multivariable Space‐Time Data

  2021cites this paper
• Collusion Detection and Ground Truth Inference in Crowdsourcing for Labeling Tasks

  2021cites this paper
• Statistical Network Analysis with Bergm

  2021cites this paper
• Adjusted composite likelihood for robust Bayesian meta-analysis

  2021influential citation
• General Bayesian L 2 calibration of mathematical models

  2021influential citation
• Maximum composite likelihood estimation for spatial extremes models of Brown–Resnick type with application to precipitation data

  2021cites this paper
• General Bayesian L2 calibration of mathematical models

  2021influential citation
• Distributed Bayesian Kriging

  2021cites this paper
• Composite likelihood inference for ordinal periodontal data with replicated spatial patterns

  2021cites this paper
• Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes

  2020cites this paper
• Modeling short‐ranged dependence in block extrema with application to polar temperature data

  2020cites this paper
• Advances in statistical modeling of spatial extremes

  2020cites this paper
• 30 Years of space–time covariance functions

  2020cites this paper
• Regularization of Bayesian quasi-likelihoods constructed from complex estimating functions

  2020cites this paper
• Pseudo Bayesian Estimation of One-way ANOVA Model in Complex Surveys

  2020influential citation
• Penalized composite likelihood for colored graphical Gaussian models

  2020cites this paper
• Composite mixture of log-linear models for categorical data

  2020cites this paper
• Composite likelihood methods for large Bayesian VARs with stochastic volatility

  2020cites this paper
• A Bayesian semi-parametric hybrid model for spatial extremes with unknown dependence structure

  2020cites this paper
• Nonstationary cross-covariance functions for multivariate spatio-temporal random fields

  2020cites this paper
• A Bayesian Framework for the Multiscale Assessment of Storm Severity and Related Uncertainties

  2020cites this paper
• Do small and large floods have the same drivers of change? A regional attribution analysis in Europe

  2020influential citation
• Uncertainty Estimation for Pseudo‐Bayesian Inference Under Complex Sampling

  2020cites this paper
• Integrating Climatic and Physical Information in a Bayesian Hierarchical Model of Extreme Daily Precipitation

  2020cites this paper
• On the distribution of maximum crest and wave height at intermediate water depths

  2020influential citation
• Bayesian Spatial Clustering of Extremal Behavior for Hydrological Variables

  2019cites this paper
• On spatial conditional extremes for ocean storm severity

  2019influential citation
• Nonstationarity in peaks‐over‐threshold river flows: A regional random effects model

  2019cites this paper
• Generalized Variational Inference: Three arguments for deriving new Posteriors

  2019cites this paper
• Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors

  2019influential citation
• Dealing with misspecification in structural macroeconometric models

  2019cites this paper
• Contributions to Likelihood-Based Modelling of Extreme Values

  2019cites this paper
• Unit Level Modeling of Survey Data for Small Area Estimation Under Informative Sampling: A Comprehensive Overview with Extensions

  2019cites this paper
• Flood trends in Europe: are changes in small and big floods different?

  2019influential citation
• Strong Consistency of Nonparametric Bayesian Inferential Methods for Multivariate Max-Stable Distributions

  2019cites this paper
• Bayesian Mixed Effects Model Estimation under Informative Sampling

  2019cites this paper
• Comparative Analysis of Bayesian Methods for Estimation of Locally-Invariant Extremes

  2019cites this paper
• Pseudo Bayesian Mixed Models under Informative Sampling

  2019cites this paper
• Spatial Extremes

  2019cites this paper
• Multi-resolution Multi-task Gaussian Processes

  2019influential citation
• Stochastic Rainfall Modeling at Sub‐kilometer Scale

  2018cites this paper
• Logistic Bayesian LASSO for detecting association combining family and case-control data

  2018cites this paper
• Bayesian modeling of air pollution extremes using nested multivariate max‐stable processes

  2018cites this paper
• ABC and Indirect Inference

  2018influential citation
• Bayesian Uncertainty Estimation Under Complex Sampling

  2018influential citation
• Improved Return Level Estimation via a Weighted Likelihood, Latent Spatial Extremes Model

  2018influential citation
• Sklar’s Omega: A Gaussian copula-based framework for assessing agreement

  2018cites this paper
• sklarsomega: An R Package for Measuring Agreement Using Sklar's Omega Coefficient.

  2018cites this paper
• Estimation of intensity–duration–frequency curves using max-stable processes

  2018cites this paper
• Validity and accuracy of posterior distributions in Bayesian statistics

  2018cites this paper
• A note on predictive densities based on composite likelihood methods

  2018cites this paper
• Composite likelihood model comparison test under fixed and local alternatives

  2018influential citation
• A multiscaling-based intensity-duration-frequency model for extreme precipitation

  2018cites this paper
• Using Kriging with a heterogeneous measurement error to improve the accuracy of extreme precipitation return level estimation

  2018cites this paper
• Statistical models for extreme weather events

  2018cites this paper