Copertina

Approximate Likelihood-Based Inference for Spatial Generalized Linear Mixed Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Watson, Samuel I., Wang, Yixin, Giorgi, Emanuele
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Generalised Linear Mixed Model Specification, Analysis, Fitting, and Optimal Design in R with the glmmr Packages
di: Watson, Samuel I.
Pubblicazione: (2023)

Differentially Private One-Shot Federated Inference for Linear Mixed Models via Lossless Likelihood Reconstruction
di: Hanada, Keisuke, et al.
Pubblicazione: (2026)

Scalable Bayesian Inference for Generalized Linear Mixed Models via Stochastic Gradient MCMC
di: Berchuck, Samuel I., et al.
Pubblicazione: (2024)

Robust Inference for Generalized Linear Mixed Models: An Approach Based on Score Sign Flipping
di: Andreella, Angela, et al.
Pubblicazione: (2024)

Marginal Inference for Hierarchical Generalized Linear Mixed Models with Patterned Covariance Matrices Using the Laplace Approximation
di: Hoef, Jay M. Ver, et al.
Pubblicazione: (2023)

Quasi-maximum Likelihood Inference for Linear Double Autoregressive Models
di: Liu, Hua, et al.
Pubblicazione: (2020)

Re-thinking Spatial Confounding in Spatial Linear Mixed Models
di: Khan, Kori, et al.
Pubblicazione: (2023)

A flexible class of latent variable models for the analysis of antibody response data
di: Giorgi, Emanuele, et al.
Pubblicazione: (2025)

Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
di: Zhang, Tianni, et al.
Pubblicazione: (2026)

Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
di: Cheng, Si, et al.
Pubblicazione: (2023)

Generalized Bayesian Likelihood-Free Inference
di: Pacchiardi, Lorenzo, et al.
Pubblicazione: (2021)

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models
di: Baek, Youngsoo, et al.
Pubblicazione: (2026)

Exact Gradient Evaluation for Adaptive Quadrature Approximate Marginal Likelihood in Mixed Models for Grouped Data
di: Stringer, Alex
Pubblicazione: (2023)

Approximate Maximum Likelihood Inference for Acoustic Spatial Capture-Recapture with Unknown Identities, Using Monte Carlo Expectation Maximization
di: Wang, Yuheng, et al.
Pubblicazione: (2024)

RESAPLE: An Approximate One-Step Restricted Likelihood Estimator of Spatial Dependence for Exploratory Spatial Analysis
di: Khan, Aditya, et al.
Pubblicazione: (2026)

A Generalized Tangent Approximation based Variational Inference Framework for Strongly Super-Gaussian Likelihoods
di: Roy, Somjit, et al.
Pubblicazione: (2025)

Efficient Bayesian Inference for Spatial Point Patterns Using the Palm Likelihood
di: Collins, Kevin M., et al.
Pubblicazione: (2025)

A Time-Series Model for Areal Data Using Spatially Correlated Gaussian Processes
di: Posada, Alejandro Rozo, et al.
Pubblicazione: (2025)

A Scalable Variational Bayes Approach to Fit High-dimensional Spatial Generalized Linear Mixed Models
di: Lee, Jin Hyung, et al.
Pubblicazione: (2024)

A Deep Learning Synthetic Likelihood Approximation of a Non-stationary Spatial Model for Extreme Streamflow Forecasting
di: Majumder, Reetam, et al.
Pubblicazione: (2022)

Random Effects Misspecification and its Consequences for Prediction in Generalized Linear Mixed Models
di: Vu, Quan, et al.
Pubblicazione: (2024)

Methods of Selective Inference for Linear Mixed Models: a Review and Empirical Comparison
di: D'Alessandro, Matteo, et al.
Pubblicazione: (2025)

Likelihood-Free Inference via Structured Score Matching
di: Jiang, Haoyu, et al.
Pubblicazione: (2026)

Distributed Empirical Likelihood Inference With or Without Byzantine Failures
di: Wang, Qihua, et al.
Pubblicazione: (2024)

When Composite Likelihood Meets Stochastic Approximation
di: Alfonzetti, Giuseppe, et al.
Pubblicazione: (2023)

Empirical Likelihood Inference over Decentralized Networks
di: Du, Jinye, et al.
Pubblicazione: (2024)

Data-Driven Influence Functions for Optimization-Based Causal Inference
di: Jordan, Michael I., et al.
Pubblicazione: (2022)

Efficient Bayesian Inference in the Cox Model via Rank-Ordered Likelihood
di: Ohigashi, Tomohiro, et al.
Pubblicazione: (2026)

Alternative Likelihood Approximations for High-Dimensional Intervals for Lasso
di: Harris, Logan, et al.
Pubblicazione: (2025)

Pseudo-Empirical Likelihood Methods for Causal Inference
di: Huang, Jingyue, et al.
Pubblicazione: (2024)

Sample Empirical Likelihood Methods for Causal Inference
di: Huang, Jingyue, et al.
Pubblicazione: (2024)

High Dimensional Gaussian and Bootstrap Approximations in Generalized Linear Models
di: Choudhury, Mayukh, et al.
Pubblicazione: (2026)

An Approximate Identity Link Function for Bayesian Generalized Linear Models
di: Hamura, Yasuyuki
Pubblicazione: (2024)

Inference for Heterogeneous Graphical Models using Doubly High-Dimensional Linear-Mixed Models
di: Yue, Kun, et al.
Pubblicazione: (2024)

Inference on the Significance of Modalities in Multimodal Generalized Linear Models
di: Jin, Wanting, et al.
Pubblicazione: (2026)

G-HIVE: Parameter Estimation and Approximate Inference for Multivariate Response Generalized Linear Models with Hidden Variables
di: Lee, Inbeom, et al.
Pubblicazione: (2025)

Empirical Likelihood Meets Prediction-Powered Inference
di: Wang, Guanghui, et al.
Pubblicazione: (2025)

Exact Posterior Mean and Covariance for Generalized Linear Mixed Models
di: Zhang, Tonglin
Pubblicazione: (2024)

Selective Inference in Graphical Models via Maximum Likelihood
di: Guglielmini, Sofia, et al.
Pubblicazione: (2025)

A decay-adjusted spatio-temporal model to account for the impact of mass drug administration on neglected tropical disease prevalence
di: Giorgi, Emanuele, et al.
Pubblicazione: (2025)