A double varying-coefficient modeling approach for analyzing longitudinal observations
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Publication:2274194
DOI10.1007/s10255-019-0840-8zbMath1429.62118OpenAlexW2964054790WikidataQ127459037 ScholiaQ127459037MaRDI QIDQ2274194
Publication date: 19 September 2019
Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10255-019-0840-8
spline approximationlocally linearautoregressive processdouble varying coefficientirregular time quantum
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
Cites Work
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- Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data
- A practical guide to splines
- Variable selection in quantile varying coefficient models with longitudinal data
- Efficient semiparametric regression for longitudinal data with nonparametric covariance estimation
- Variable selection and estimation in high-dimensional varying-coefficient models
- A moving average Cholesky factor model in covariance modelling for longitudinal data
- Semiparametric Longitudinal Model with Irregular Time autoregressive error process
- M-estimation and B-spline approximation for varying coefficient models with longitudinal data
- Weak and strong uniform consistency of kernel regression estimates
- Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data
- Empirical-Bias Bandwidths for Local Polynomial Nonparametric Regression and Density Estimation
- Semiparametric Regression for Clustered Data Using Generalized Estimating Equations
- Parsimonious Covariance Matrix Estimation for Longitudinal Data
- Asymptotic Confidence Regions for Kernel Smoothing of a Varying-Coefficient Model with Longitudinal Data
- Informative Estimation and Selection of Correlation Structure for Longitudinal Data
- Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
- Semiparametric Mean–Covariance Regression Analysis for Longitudinal Data
- Analysis of Longitudinal Data With Semiparametric Estimation of Covariance Function
- Empirical Likelihood for a Varying Coefficient Model With Longitudinal Data
- Semiparametric Estimation of Covariance Matrixes for Longitudinal Data
- Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
- Semiparametric Time-Varying Coefficients Regression Model for Longitudinal Data
- Quadratic Inference Functions for Varying‐Coefficient Models with Longitudinal Data
- New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
- Efficient Semiparametric Marginal Estimation for Longitudinal/Clustered Data
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