Copula and composite quantile regression-based estimating equations for longitudinal data
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Publication:2042520
DOI10.1007/S10463-020-00756-1zbMath1469.62240OpenAlexW3032126056MaRDI QIDQ2042520
Publication date: 20 July 2021
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-020-00756-1
Nonparametric regression and quantile regression (62G08) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Cites Work
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- Longitudinal data analysis using generalized linear models
- Automatic variable selection for longitudinal generalized linear models
- Variable selection in robust regression models for longitudinal data
- Long-tail longitudinal modeling of insurance company expenses
- Robust empirical likelihood inference for generalized partial linear models with longitudinal data
- Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data
- Efficient parameter estimation and variable selection in partial linear varying coefficient quantile regression model with longitudinal data
- Efficient parameter estimation via Gaussian copulas for quantile regression with longitudinal data
- Composite quantile regression and the oracle model selection theory
- Robust estimation of covariance parameters in partial linear model for longitudinal data
- On the simplified pair-copula construction -- simply useful or too simplistic?
- Heavy-tailed longitudinal data modeling using copulas
- Quantile regression in partially linear varying coefficient models
- An efficient and robust variable selection method for longitudinal generalized linear models
- Composite quantile regression for correlated data
- Modal regression statistical inference for longitudinal data semivarying coefficient models: generalized estimating equations, empirical likelihood and variable selection
- Weighted local linear composite quantile estimation for the case of general error distributions
- Modified SEE variable selection for varying coefficient instrumental variable models
- New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
- Robust estimation in generalized semiparametric mixed models for longitudinal data
- Smooth-threshold GEE variable selection for varying coefficient partially linear models with longitudinal data
- Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
- Efficient pairwise composite likelihood estimation for spatial-clustered data
- Quasi-Likelihood for Median Regression Models
- Variable Selection in Semiparametric Quantile Modeling for Longitudinal Data
- Multivariate Dispersion Models Generated From Gaussian Copula
- Varying-coefficient models and basis function approximations for the analysis of repeated measurements
- COPULA-BASED QUANTILE REGRESSION FOR LONGITUDINAL DATA
- Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
- Modeling Longitudinal Data Using a Pair-Copula Decomposition of Serial Dependence
- Standard errors and covariance matrices for smoothed rank estimators
- New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
- Robust Estimation in Generalized Partial Linear Models for Clustered Data
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