Let {Xn ,n=>1} be a strictly stationary sequence of negatively associated random variables, with common distribution function F. In this paper, we consider the estimation of the two-dimensional distribution function of (X1, Xk+1) for fixed $K /in N$ based on kernel type estimators. We introduce asymptotic normality and properties and moments. From these we derive the optimal bandwidth...

We are concerned with solving an equation whose form is applicable to a wide class of problems arising in computer vision. The equation typically relates image point locations to the parameters of some appropriate model. We assume that each measured datum is accompanied by a covariance matrix that characterises the uncertainty of the measurement. Noisy data are assumed to be in plentiful supply...

Sparse representation of signals has been the focus of much research in the recent years. A vast majority of existing algorithms deal with vectors, and higher–order data like images are dealt with by vectorization. However, the structure of the data may be lost in the process, leading to a poorer representation and overall performance degradation. In this paper we propose a novel approach for s...

The Open University's repository of research publications and other research outputs Forecast covariances in the linear multiregression dynamic model Journal Article

The Open University's repository of research publications and other research outputs Forecast covariances in the linear multiregression dynamic model Journal Article