Parameter estimation for semiparametric ordinary differential equation models

DOI10.1080/03610926.2018.1523433OpenAlexW2907185493WikidataQ99578545 ScholiaQ99578545MaRDI QIDQ5077959

Arun Kumar, Hongqi Xue, Hulin Wu

Publication date: 20 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500512

zbMATH Keywords

ordinary differential equationtwo-stage estimationpenalized splinedata augmentation estimationsemiparametric coefficient models

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• DEDiscover
• SemiPar

Cites Work

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• Two likelihood-based semiparametric estimation methods for panel count data with covariates
• DEDiscover
• \(\sqrt{n}\)-consistent parameter estimation for systems of ordinary differential equations: bypassing numerical integration via smoothing
• Bootstrap consistency for general semiparametric \(M\)-estimation
• Asymptotic efficiency and finite-sample properties of the generalized profiling estimation of parameters in ordinary differential equations
• Estimation of constant and time-varying dynamic parameters of HIV infection in a nonlinear differential equation model
• Sieve estimation of constant and time-varying coefficients in nonlinear ordinary differential equation models by considering both numerical error and measurement error
• Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Convergence rate of sieve estimates
• On methods of sieves and penalization
• Weak convergence and empirical processes. With applications to statistics
• Parameter estimation of ODE's via nonparametric estimators
• Robust semiparametric M-estimation and the weighted bootstrap
• Estimation of parameters in incomplete data models defined by dynamical systems
• Numerical Discretization-Based Estimation Methods for Ordinary Differential Equation Models via Penalized Spline Smoothing with Applications in Biomedical Research
• Estimation and Inference for a Spline-Enhanced Population Pharmacokinetic Model
• Solving Ordinary Differential Equations I
• Asymptotic properties of penalized spline estimators
• On the asymptotics of penalized splines
• Efficient Local Estimation for Time-Varying Coefficients in Deterministic Dynamic Models With Applications to HIV-1 Dynamics
• A Spline Least Squares Method for Numerical Parameter Estimation in Differential Equations
• Semiparametric Regression
• Parameter estimation of ordinary differential equations
• Ordinary Differential Equations in Theory and Practice
• Parameter Estimation for Differential Equations: a Generalized Smoothing Approach
• Parameter Estimation for Differential Equation Models Using a Framework of Measurement Error in Regression Models
• Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
• Sieve Maximum Likelihood Estimator for Semiparametric Regression Models With Current Status Data

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