AbstractIn this note, the authors propose a new nonparametric method of estimation of density using orthonormal systems iteratively. The asymptotic mean integrated square error of the estimate at each stage is less than or equal to that of the preceding stage. The new estimate is better, in some cases, than the traditional estimate based upon orthonormal functions from the point of view of the mean integrated square error in the limit
This thesis advocates the use of shrinkage and penalty techniques for estimating the parameters of a...
This paper .rst establishes consistency of the exponential series density estimator when nuisance pa...
AbstractThe problem of nonparametric estimation of a multivariate density function is addressed. In ...
AbstractIn this note, the authors propose a new nonparametric method of estimation of density using ...
In this note, the authors propose a new nonparametric method of estimation of density using orthonor...
AbstractIn this paper, the authors studied certain properties of the estimate of Liang and Krishnaia...
AbstractIn this paper, an iterative estimate of the multivariate density is proposed when the variab...
In Wegman\u27s paper [5] on nonparametric density estimation, he states that it would be interesting...
In this article we propose two new Multiplicative Bias Correction (MBC) techniques for nonparametric...
We present a novel nonparametric density estimator and a new data-driven bandwidth selection method ...
The object of the present study is to summarize recent developments in nonparametric density estimat...
In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is...
International audienceIn statistics, it is usually difficult to estimate the probability density fun...
Density estimation has a long history in statistics. There are two main approaches to density, estim...
AbstractWe compare the merits of two orthogonal series methods of estimating a density and its deriv...
This thesis advocates the use of shrinkage and penalty techniques for estimating the parameters of a...
This paper .rst establishes consistency of the exponential series density estimator when nuisance pa...
AbstractThe problem of nonparametric estimation of a multivariate density function is addressed. In ...
AbstractIn this note, the authors propose a new nonparametric method of estimation of density using ...
In this note, the authors propose a new nonparametric method of estimation of density using orthonor...
AbstractIn this paper, the authors studied certain properties of the estimate of Liang and Krishnaia...
AbstractIn this paper, an iterative estimate of the multivariate density is proposed when the variab...
In Wegman\u27s paper [5] on nonparametric density estimation, he states that it would be interesting...
In this article we propose two new Multiplicative Bias Correction (MBC) techniques for nonparametric...
We present a novel nonparametric density estimator and a new data-driven bandwidth selection method ...
The object of the present study is to summarize recent developments in nonparametric density estimat...
In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is...
International audienceIn statistics, it is usually difficult to estimate the probability density fun...
Density estimation has a long history in statistics. There are two main approaches to density, estim...
AbstractWe compare the merits of two orthogonal series methods of estimating a density and its deriv...
This thesis advocates the use of shrinkage and penalty techniques for estimating the parameters of a...
This paper .rst establishes consistency of the exponential series density estimator when nuisance pa...
AbstractThe problem of nonparametric estimation of a multivariate density function is addressed. In ...