AbstractIn this paper, an iterative estimate of the multivariate density is proposed when the variables are binary in nature. Some properties of this estimate are also discussed. Finally, applications of this estimate are discussed in the areas of pattern recognition and reliability
AbstractWe consider the problem of estimating the support of a multivariate density based on contami...
AbstractWe consider estimation of a multivariate probability density function f(x) by kernel type ne...
In this paper we explore a method for modeling of categorical data derived from the principles of th...
In this paper, an iterative estimate of the multivariate density is proposed when the variables are ...
AbstractIn this paper, the authors studied certain properties of the estimate of Liang and Krishnaia...
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...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
The problem of nonparametric estimation of the joint probability density of a vector of continuous a...
In this work, three extensions of univariate nonparametric probability density estimators into two d...
In this article we propose two new Multiplicative Bias Correction (MBC) techniques for nonparametric...
This paper presents an algorithm for efficient multivariate density estimation, using a blockized im...
We consider the problem of multivariate density estimation, using samples from the distribution of i...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
AbstractWe consider the problem of estimating the support of a multivariate density based on contami...
AbstractWe consider estimation of a multivariate probability density function f(x) by kernel type ne...
In this paper we explore a method for modeling of categorical data derived from the principles of th...
In this paper, an iterative estimate of the multivariate density is proposed when the variables are ...
AbstractIn this paper, the authors studied certain properties of the estimate of Liang and Krishnaia...
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...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
The problem of nonparametric estimation of the joint probability density of a vector of continuous a...
In this work, three extensions of univariate nonparametric probability density estimators into two d...
In this article we propose two new Multiplicative Bias Correction (MBC) techniques for nonparametric...
This paper presents an algorithm for efficient multivariate density estimation, using a blockized im...
We consider the problem of multivariate density estimation, using samples from the distribution of i...
We propose a new nonparametric estimator for the density function of multivariate bounded data. As f...
AbstractWe consider the problem of estimating the support of a multivariate density based on contami...
AbstractWe consider estimation of a multivariate probability density function f(x) by kernel type ne...
In this paper we explore a method for modeling of categorical data derived from the principles of th...
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