Ara
Toplam kayıt 26, listelenen: 11-20
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 ...
Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data
(Natl Inst Statistics, 2017)
In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya-Watson (Nadarya, 1964; Watson, 1964) type kernel estimator. In this estimation procedure, the censored observations are ...
Smoothing parameter selection in semiparametric regression models with censored data
(Inst Advanced Science Extension, 2017)
In this paper, we introduce penalized spline estimators for the unknown function and a parameter vector in a semiparametric regression model with right censored data. In order to obtain this estimator accurately and ...
Right-Censored Nonparametric Regression: A Comparative Simulation Study
(Assoc Information Communication Technology Education & Science, 2016)
This paper introduces the operating of the selection criteria for right-censored nonparametric regression using smoothing spline. In order to transform the response variable into a variable that contains the right-censorship, ...
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 ...
Consistency and Asymptotic Normality of Estimator for Parameters in Multiresponse Multipredictor Semiparametric Regression Model
(MDPI, 2022)
A multiresponse multipredictor semiparametric regression (MMSR) model is a combination of parametric and nonparametric regressions models with more than one predictor and response variables where there is correlation between ...
Semiparametric Time-Series Model Using Local Polynomial: An Application on the Effects of Financial Risk Factors on Crop Yield
(MDPI, 2022)
This paper proposes a semiparametric local polynomial estimator for modelling agricultural time-series. We consider the modelling of the crop yield variable according to determined financial risk factors in Turkey. The ...
Reproducing Kernel Hilbert Space Approach to Multiresponse Smoothing Spline Regression Function
(MDPI, 2022)
In statistical analyses, especially those using a multiresponse regression model approach, a mathematical model that describes a functional relationship between more than one response variables and one or more predictor ...