Qui [1] discussed the estimation problem of jump regression functions which were divided into eight types. L2consistent estimates of two types of them were obtained. This paper studies further this topics and obtains L2 consistent estimates of the other four types. For the last two types, the authors also put forwards an estimate. A little numerical results are also given. 1
[[abstract]]A new procedure is proposed to estimate the jump location curve and surface in the two-d...
Consistency, Jump-preserving estimation, Local linear fit, Nonparametric regression, Smoothing, Weig...
Wavelets are applied to detect the jumps in a heteroscedastic regression model. It is shown that the...
This paper suggests an estimator of the number of jumps of the jump regression functions. The estima...
Regression analysis is a method of estimating the mean of response variable as a function of other e...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
In this paper, we discuss estimation of bivariate jump regression functions. An a.s. consistent esti...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
We develop robust inference methods for studying linear dependence between the jumps of discretely o...
This paper deals with nonparametric estimation of a regression curve, where the estimation method sh...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
summary:We establish consistent estimators of jump positions and jump altitudes of a multi-level ste...
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
In this paper, we introduce the method of leaps and bounds regression which can be used to select va...
The authors consider the M-type estimators of regression function and show their almost-sure consist...
[[abstract]]A new procedure is proposed to estimate the jump location curve and surface in the two-d...
Consistency, Jump-preserving estimation, Local linear fit, Nonparametric regression, Smoothing, Weig...
Wavelets are applied to detect the jumps in a heteroscedastic regression model. It is shown that the...
This paper suggests an estimator of the number of jumps of the jump regression functions. The estima...
Regression analysis is a method of estimating the mean of response variable as a function of other e...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
In this paper, we discuss estimation of bivariate jump regression functions. An a.s. consistent esti...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
We develop robust inference methods for studying linear dependence between the jumps of discretely o...
This paper deals with nonparametric estimation of a regression curve, where the estimation method sh...
We study the asymptotics for jump-penalized least squares regression aiming at approximating a regre...
summary:We establish consistent estimators of jump positions and jump altitudes of a multi-level ste...
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
In this paper, we introduce the method of leaps and bounds regression which can be used to select va...
The authors consider the M-type estimators of regression function and show their almost-sure consist...
[[abstract]]A new procedure is proposed to estimate the jump location curve and surface in the two-d...
Consistency, Jump-preserving estimation, Local linear fit, Nonparametric regression, Smoothing, Weig...
Wavelets are applied to detect the jumps in a heteroscedastic regression model. It is shown that the...