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
Non-parametric density estimation is the problem of approximating the values of a probability densit...
Tech ReportThe nonparametric density estimation method proposed in this paper is computationally fas...
If x([1],) ..., x([n]) are the ordered outcomes of an independent random sample from a distribution ...
In this note, the authors propose a new nonparametric method of estimation of density using orthonor...
AbstractIn this note, the authors propose a new nonparametric method of estimation of density using ...
The application of nonparametric probability density function estimation for the purpose of data ana...
Key words and phrases Nonparametric density estimation monotone density symmetric unimodal density...
There exist many ways to estimate the shape of the underlying density. Generally, we can categorize ...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
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...
New nonparametric procedure for estimating the probability density function of a positive random var...
The object of the present study is to summarize recent developments in nonparametric density estimat...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
Density estimation has a long history in statistics. There are two main approaches to density, estim...
Non-parametric density estimation is the problem of approximating the values of a probability densit...
Tech ReportThe nonparametric density estimation method proposed in this paper is computationally fas...
If x([1],) ..., x([n]) are the ordered outcomes of an independent random sample from a distribution ...
In this note, the authors propose a new nonparametric method of estimation of density using orthonor...
AbstractIn this note, the authors propose a new nonparametric method of estimation of density using ...
The application of nonparametric probability density function estimation for the purpose of data ana...
Key words and phrases Nonparametric density estimation monotone density symmetric unimodal density...
There exist many ways to estimate the shape of the underlying density. Generally, we can categorize ...
A new method for bias reduction in nonparametric density estimation is proposed. The method is a sim...
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...
New nonparametric procedure for estimating the probability density function of a positive random var...
The object of the present study is to summarize recent developments in nonparametric density estimat...
We review different approaches to nonparametric density and regression estimation. Kernel estimators...
Density estimation has a long history in statistics. There are two main approaches to density, estim...
Non-parametric density estimation is the problem of approximating the values of a probability densit...
Tech ReportThe nonparametric density estimation method proposed in this paper is computationally fas...
If x([1],) ..., x([n]) are the ordered outcomes of an independent random sample from a distribution ...