Least squares estimators for reflected Ornstein–Uhlenbeck processes
H Yuecaia, Z Dingwen - Communications in Statistics-Theory and …, 2024 - Taylor & Francis
In this article, we investigate the parameter estimation problem for reflected Ornstein–
Uhlenbeck processes with mean reversion. Both estimates based on either continuously or …
Uhlenbeck processes with mean reversion. Both estimates based on either continuously or …
Nonlinear least squares estimator for generalized diffusion processes with reflecting barriers
Y Han, D Zhang - Stochastics, 2024 - Taylor & Francis
In this paper, we investigate the parameter estimation problem for generalized diffusion
processes with two-sided reflected barriers. The estimator is obtained using the nonlinear …
processes with two-sided reflected barriers. The estimator is obtained using the nonlinear …
Nadaraya-Watson estimators for stochastic differential equations driven by fractional Brownian motion
Y Han, D Zhang - Stochastic Models, 2024 - Taylor & Francis
In this article, we investigate the nonparametric Nadaraya-Watson estimator for the drift
function of stochastic differential equations driven by fractional Brownian motion of the Hurst …
function of stochastic differential equations driven by fractional Brownian motion of the Hurst …
Evaluation of the Performance of Kernel Non-parametric Regression and Ordinary Least Squares Regression
AM Sadek, LA Mohammed - JOIV: International Journal on Informatics …, 2024 - joiv.org
Researchers need to understand the differences between parametric and nonparametric
regression models and how they work with available information about the relationship …
regression models and how they work with available information about the relationship …
Local linear estimators for reflected diffusions
D Zhang - Journal of Nonparametric Statistics, 2024 - Taylor & Francis
In this paper, we investigate the nonparametric local linear estimator for the drift function of
reflected stochastic differential equations based on the discretely observed process. Under …
reflected stochastic differential equations based on the discretely observed process. Under …