Ara
Toplam kayıt 5, listelenen: 1-5
Choice of smoothing parameter for kernel type ridge estimators in semiparametric regression models
(National Statistical Institute, 2021)
This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important ...
Rational (Pade) approximation for estimating the components of the partially-linear regression model
(Taylor & Francis Inc., 2021)
This paper proposes a new smoothing technique based on rational function approximation using truncated total least squares (P - TTLS) and compares it with the widely used smoothing spline method, which has become a very ...
Kernel Ridge Estimator for the Partially Linear Model under Right-Censored Data
(IRANIAN STATISTICAL SOC, 2021)
Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity ...
Comparison of parametric and semi-parametric models with randomly right-censored data by weighted estimators: Two applications in colon cancer and hepatocellular carcinoma datasets
(SAGE Publications Inc., 2021)
In this study, parametric and semi-parametric regression models are examined for random right censorship. The components of the aforementioned regression models are estimated with weights based on Cox and Kaplan-Meier ...
Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator
(MDPI, 2021)
This paper focuses on the adaptive spline (A-spline) fitting of the semiparametric regression model to time series data with right-censored observations. Typically, there are two main problems that need to be solved in ...