I few years ago, while I was working on kernel based density estimation on compact support distribution (like copulas) I went through a series of papers on circular distributions. By that time, I thought it was something for mathematicians working on weird spaces.... but during the past weeks, I saw several potential applications of those estimators. circular data density estimation Consider the density of an angle say, i.e. a function such that with a circular relationship, i.e. . It can ..
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
This dissertation focuses mainly on directional data in two dimensions, called ``circular data," bec...
In this paper we derive asymptotic expressions for the mean integrated squared error of a class of d...
Until now the problem of estimating circular densities when data are observed with errors has been m...
Kernel density estimation for multivariate, circular data has been formulated only when the sample s...
This paper aims to introduce an estimation algorithm for the joint densityof a circular-circular ran...
The circular kernel density estimator, with the wrapped Cauchy kernel, is derived from the empirical...
Nearest neighbour methods traditionally used to estimate density of a sessile biological population ...
Predictive density for a future observation is derived when the given data comes from circular or sp...
Angles, directions, events, occurrences along time... all of them can be viewed as data on a circle...
The conditional density offers the most informative summary of the relationship between explanatory ...
We consider the problem of nonparametrically estimating a circular density from data contaminated by...
We propose estimating equations whose unknown parameters are the values taken by a circular density ...
AbstractUntil now the problem of estimating circular densities when data are observed with errors ha...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
This dissertation focuses mainly on directional data in two dimensions, called ``circular data," bec...
In this paper we derive asymptotic expressions for the mean integrated squared error of a class of d...
Until now the problem of estimating circular densities when data are observed with errors has been m...
Kernel density estimation for multivariate, circular data has been formulated only when the sample s...
This paper aims to introduce an estimation algorithm for the joint densityof a circular-circular ran...
The circular kernel density estimator, with the wrapped Cauchy kernel, is derived from the empirical...
Nearest neighbour methods traditionally used to estimate density of a sessile biological population ...
Predictive density for a future observation is derived when the given data comes from circular or sp...
Angles, directions, events, occurrences along time... all of them can be viewed as data on a circle...
The conditional density offers the most informative summary of the relationship between explanatory ...
We consider the problem of nonparametrically estimating a circular density from data contaminated by...
We propose estimating equations whose unknown parameters are the values taken by a circular density ...
AbstractUntil now the problem of estimating circular densities when data are observed with errors ha...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
We investigate kernel density estimation where the kernel function varies from point to point. Densi...
This dissertation focuses mainly on directional data in two dimensions, called ``circular data," bec...
In this paper we derive asymptotic expressions for the mean integrated squared error of a class of d...