This paper considers a class of local likelihood methods produced by Eguchi and Copas. Unified asymptotic results are presented in the usual smoothing context of the bandwith, h, tending to zero as the sample size tends to infinity. We present our results pointwise in the univariate case, but then go on to extend them to global properties and to indicate how to cope with the multivariate case. Specific members of the class due to Copas, and Hjort and Jones are seen to be members of a subset of the whole class with the same, and best, small h behavior. Further comparions between members of the class are alluded to based on the complementary large h asymptotic results of Eguchi and Copas
Département d’Informatique et Recherche Opérationnelle We describe an interesting application of the...
Abstract. In this paper, we obtain asymptotic confidence bands for both the density and regression f...
在非參數判別分析中,我們利用區間Logistic迴歸模型 (Local logistic regression)估計貝氏準則的事後機率。在進行區間Logistic迴歸時,我們需要決定平滑參數值,我們取...
Methods for probability density estimation are traditionally classified as either parametric or non-...
Recent papers of Copas (1995), Hjort and Jones (1996) and Loader (1996) have developed closely relat...
The local maximum likelihood estimate (t) of a parameter in a statistical model f(x, theta) is defin...
By drawing an analogy with likelihood for censored data, a local likelihood function is proposed whi...
Paper 1 ”Bias and bandwidth for local likelihood density estimation”: A local likelihood density est...
The paper presents a unified approach to local likelihood estimation for a broad class of nonparamet...
This paper develops a nonparametric density estimator with parametric overtones. Suppose f(x, θ) is ...
Two existing density estimators based on local likelihood have properties that are comparable to t...
This paper presents a new method for spatially adaptive local (constant) likelihood estimation which...
The local likelihood estimator and a semiparametric bootstrap method are studied under weaker condit...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
A novel semiparametric estimator for the probability density function of detected distances in line ...
Département d’Informatique et Recherche Opérationnelle We describe an interesting application of the...
Abstract. In this paper, we obtain asymptotic confidence bands for both the density and regression f...
在非參數判別分析中,我們利用區間Logistic迴歸模型 (Local logistic regression)估計貝氏準則的事後機率。在進行區間Logistic迴歸時,我們需要決定平滑參數值,我們取...
Methods for probability density estimation are traditionally classified as either parametric or non-...
Recent papers of Copas (1995), Hjort and Jones (1996) and Loader (1996) have developed closely relat...
The local maximum likelihood estimate (t) of a parameter in a statistical model f(x, theta) is defin...
By drawing an analogy with likelihood for censored data, a local likelihood function is proposed whi...
Paper 1 ”Bias and bandwidth for local likelihood density estimation”: A local likelihood density est...
The paper presents a unified approach to local likelihood estimation for a broad class of nonparamet...
This paper develops a nonparametric density estimator with parametric overtones. Suppose f(x, θ) is ...
Two existing density estimators based on local likelihood have properties that are comparable to t...
This paper presents a new method for spatially adaptive local (constant) likelihood estimation which...
The local likelihood estimator and a semiparametric bootstrap method are studied under weaker condit...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
A novel semiparametric estimator for the probability density function of detected distances in line ...
Département d’Informatique et Recherche Opérationnelle We describe an interesting application of the...
Abstract. In this paper, we obtain asymptotic confidence bands for both the density and regression f...
在非參數判別分析中,我們利用區間Logistic迴歸模型 (Local logistic regression)估計貝氏準則的事後機率。在進行區間Logistic迴歸時,我們需要決定平滑參數值,我們取...