Frequentist conditional variance for nonlinear mixed-effects models

DOI10.1007/s42519-022-00304-5OpenAlexW4308545243MaRDI QIDQ2096413

Nan Zheng, Noel Cadigan

Publication date: 16 November 2022

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42519-022-00304-5

zbMATH Keywords

prediction errorconfidence intervalstate-space modelnonlinear mixed-effects modeltemplate model builder

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Parametric inference (62Fxx) Nonparametric inference (62Gxx)

Uses Software

• MIXED
• ADMB
• AD Model Builder
• PROC NLMIXED
• TMB
• spict

Cites Work

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• Computing the nearest correlation matrix--a problem from finance
• On particle methods for parameter estimation in state-space models
• Straightforward intermediate rank tensor product smoothing in mixed models
• Consistency and asymptotic normality of the maximum likelihood estimator in generalized linear models
• Integrated likelihood methods for eliminating nuisance parameters. (With comments and a rejoinder).
• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• A flexible approach to inference in semiparametric regression models with correlated errors using Gaussian processes
• Inferences in semi-parametric dynamic mixed models for longitudinal count data
• Smoothing and mixed models
• Inference and computation with generalized additive models and their extensions
• Frequentist delta-variance approximations with mixed-effects models and TMB
• Integrated likelihood inference in semiparametric regression models
• Nonparametric smoothing using state space techniques
• AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models
• Coverage Properties of Confidence Intervals for Generalized Additive Model Components
• Prediction of Random Effects in Linear and Generalized Linear Models under Model Misspecification
• Multivariate Multilevel Nonlinear Mixed Effects Models for Timber Yield Predictions
• Dirichlet–Laplace Priors for Optimal Shrinkage
• Integrated likelihood functions for non-Bayesian inference