Some bootstrap methods in nonlinear mixed-effect models

DOI10.1016/S0378-3758(98)00145-1zbMath0943.62036OpenAlexW2076881231MaRDI QIDQ1298956

Alok Krishen, Shubhabrata Das

Publication date: 10 September 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(98)00145-1

zbMATH Keywords

resamplingheteroscedasticityfixed effectsrandom effectsjackknife

Mathematics Subject Classification ID

General nonlinear regression (62J02) Nonparametric statistical resampling methods (62G09)

Related Items (2)

Weighted composite quantile regression for longitudinal mixed effects models with application to AIDS studies ⋮ Likelihood-based quantile mixed effects models for longitudinal data with multiple features via MCEM algorithm

Cites Work

• Unnamed Item
• Bootstrap procedures under some non-i.i.d. models
• Bootstrapping regression models
• Efficiency and robustness in resampling
• Bootstrap methods: another look at the jackknife
• Jackknife, bootstrap and other resampling methods in regression analysis
• A maximum likelihood estimation method for random coefficient regression models

This page was built for publication: Some bootstrap methods in nonlinear mixed-effect models