Epanechnikov kernel, Local polynomial regression, Non-invertible moving average processes,
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
The paper gives an introduction to theory and application of multivariate and semipara metric kernel...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
none2This paper establishes the conditions under which the generalised least squares estimator of th...
The paper establishes the conditions under which the generalised least squares estimator of the regr...
none2This paper is concerned with the equivalence of the weighted least squares estimators (WLSE) an...
In a standard linear model, we assume that . Alternatives can be considered, when the linear assumpt...
This paper shows the formal equivalence of Kalman filtering and smoothing techniques to generalized ...
This chapter provides an introduction to smoothing methods in time series analysis, namely local pol...
Kernel smoothing, Local linear regression, Semiparametric density estimation, Transformations,
This article studies weighted, generalized, least squares estimators in simple linear regression wit...
This article studies weighted, generalized, least squares estimators in simple linear regression wit...
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. ...
Masry (1996b) provides estimation bias and variance expression for a general local polynomial kernel...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
The paper gives an introduction to theory and application of multivariate and semipara metric kernel...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
none2This paper establishes the conditions under which the generalised least squares estimator of th...
The paper establishes the conditions under which the generalised least squares estimator of the regr...
none2This paper is concerned with the equivalence of the weighted least squares estimators (WLSE) an...
In a standard linear model, we assume that . Alternatives can be considered, when the linear assumpt...
This paper shows the formal equivalence of Kalman filtering and smoothing techniques to generalized ...
This chapter provides an introduction to smoothing methods in time series analysis, namely local pol...
Kernel smoothing, Local linear regression, Semiparametric density estimation, Transformations,
This article studies weighted, generalized, least squares estimators in simple linear regression wit...
This article studies weighted, generalized, least squares estimators in simple linear regression wit...
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. ...
Masry (1996b) provides estimation bias and variance expression for a general local polynomial kernel...
In this paper a new estimator for nonparametric regression is suggested. It is a smoothing-splines-l...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
The paper gives an introduction to theory and application of multivariate and semipara metric kernel...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
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