Estimation of ordinary differential equation parameters using constrained local polynomial regression
نویسندگان
چکیده
منابع مشابه
Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.
We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unkno...
متن کاملSparse Estimation in Ordinary Differential Equation Systems
Ordinary differential equation systems are used to model abundances of chemical species as deterministic continuous time processes. Identification of the system from noisy data is a major challenge with applications in systems biology – such as to the inference of phosphoprotein interaction networks as in [3]. For mass action kinetics the system structure – the network – is encoded via sparsity...
متن کاملRobust estimation for ordinary differential equation models.
Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a n...
متن کاملLocal Polynomial Regression for Small Area Estimation
Estimation of small area means in the presence of area level auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. The assumptions on the area level regression are considerably weaker than standard small area models. Both the small area mean functions and the between area variance function are modeled as smooth functions of area level covar...
متن کاملNumerical Solution of Integro-Differential Equations with Local Polynomial Regression
In this paper, we try to find numerical solution of b d , . a y x p x y x g x K x t y t t y a a x b a t b d , . , a y x p x y x g x K x t y t t y a a x b a t b d x t y t t y a a or x by using Local polynomial regression (LPR) method. The numerical solution shows th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistica Sinica
سال: 2014
ISSN: 1017-0405
DOI: 10.5705/ss.2012.304