Pages that link to "Item:Q3632646"
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The following pages link to Efficient Local Estimation for Time-Varying Coefficients in Deterministic Dynamic Models With Applications to HIV-1 Dynamics (Q3632646):
Displaying 35 items.
- Estimation of nonlinear differential equation model for glucose-insulin dynamics in type I diabetic patients using generalized smoothing (Q400623) (← links)
- Analysis of variance of integro-differential equations with application to population dynamics of cotton aphids (Q486066) (← links)
- Time-varying coefficient estimation in differential equation models with noisy time-varying covariates (Q642222) (← links)
- Semiparametric modeling of autonomous nonlinear dynamical systems with application to plant growth (Q652370) (← links)
- Estimating mixed-effects differential equation models (Q892455) (← links)
- Statistical diagnosis for HIV dynamics based on mean shift outlier model (Q904934) (← links)
- Estimation of constant and time-varying dynamic parameters of HIV infection in a nonlinear differential equation model (Q977648) (← links)
- Sieve estimation of constant and time-varying coefficients in nonlinear ordinary differential equation models by considering both numerical error and measurement error (Q988009) (← links)
- Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes (Q1637514) (← links)
- Learning delay dynamics for multivariate stochastic processes, with application to the prediction of the growth rate of COVID-19 cases in the United States (Q2147790) (← links)
- A joint estimation approach to sparse additive ordinary differential equations (Q2172119) (← links)
- Bayesian inference of a directional brain network model for intracranial EEG data (Q2291289) (← links)
- Timing observations of diffusions (Q2302499) (← links)
- Bayesian inference of mixed-effects ordinary differential equations models using heavy-tailed distributions (Q2416783) (← links)
- Numerical discretization-based kernel type estimation methods for ordinary differential equation models (Q2516020) (← links)
- Inferring the unknown parameters in differential equation by Gaussian process regression with constraint (Q2675742) (← links)
- Investigate Data Dependency for Dynamic Gene Regulatory Network Identification through High-dimensional Differential Equation Approach (Q2821005) (← links)
- Parameter Estimation of Partial Differential Equation Models (Q2861813) (← links)
- Robust estimation for ordinary differential equation models (Q2893386) (← links)
- Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research (Q2912324) (← links)
- A two-stage estimation method for random coefficient differential equation models with application to longitudinal HIV dynamic data (Q3094079) (← links)
- On the selection of ordinary differential equation models with application to predator‐prey dynamical models (Q3465737) (← links)
- Estimating direction fields in autonomous equation models, with an application to system identification from cross-sectional data (Q4323532) (← links)
- Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling (Q4975410) (← links)
- Generalized Ordinary Differential Equation Models (Q4975636) (← links)
- Parameter estimation for semiparametric ordinary differential equation models (Q5077959) (← links)
- Bayesian estimation of time-varying parameters in ordinary differential equation models with noisy time-varying covariates (Q5082564) (← links)
- Adaptive Semiparametric Bayesian Differential Equations Via Sequential Monte Carlo (Q5084458) (← links)
- Asymptotic Theory of \(\boldsymbol \ell _1\) -Regularized PDE Identification from a Single Noisy Trajectory (Q5097857) (← links)
- Bayesian penalized B-spline estimation approach for epidemic models (Q5106760) (← links)
- A refined parameter estimating approach for HIV dynamic model (Q5128672) (← links)
- Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach (Q5231494) (← links)
- Estimating Varying Coefficients for Partial Differential Equation Models (Q6056305) (← links)
- Manifold-constrained Gaussian process inference for time-varying parameters in dynamic systems (Q6089199) (← links)
- Differential equations in data analysis (Q6602133) (← links)
