The use of probability in system identification is shown to be equivalent to measuring Kullback-Leibler distance between the actual (empirical) and model distributions of data. When data are not known completely (being compressed, quantized, aggregated, missing etc.), the minimum distance approach can be seen as an asymptotic approximation of probabilistic inference. A class of problems is poin...

Discriminating speaking styles is an important issue in speech recognition, speaker recognition and speaker segmentation. This paper compares distance measures between Gaussian distributions for discriminating speaking styles. The Mahalanobis distance, the Bhattacharyya distance and the Kullback-Leibler divergence, which are in common use for a definition as a distance measure between Gaussian ...

In applications of differential geometry to problems of parametric inference, the notion of divergence is often used to measure the separation between two parametric densities. Among them, in this paper, we will verify measures such as Kullback-Leibler information, J-divergence, Hellinger distance, -Divergence, … and so on. Properties and results related to distance between probability d...

This paper considers the search problem, introduced by Srivastava cite{Sr}. This is a model discrimination problem. In the context of search linear models, discrimination ability of search designs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are restricted in a sense of being able to work for searching only one possibl...

We consider the problem of computing the Kullback-Leibler distance, also called the relative entropy, between a probabilistic context-free grammar and a probabilistic finite automaton. We show that there is a closed-form (analytical) solution for one part of the Kullback-Leibler distance, viz. the cross-entropy. We discuss several applications of the result to the problem of distributional appr...

Several methods that use the notion of viewpoint quality have been recently introduced in different areas of computer graphics, such as scene understanding, exploration of virtual worlds, radiosity and global illumination, image-based rendering and modelling. In this paper, we analyze the behavior of three different viewpoint quality measures. The first one is a heuristic measure, the second on...

Motivated from the bandwidth selection problem in local likelihood density estimation and from the problem of assessing a final model chosen by a certain model selection procedure, we consider estimation of the Kullback–Leibler divergence. It is known that the best bandwidth choice for the local likelihood density estimator depends on the distance between the true density and the ‘vehicle’ para...

In molecular biology, the issue of quantifying the similarity between two biological sequences is very important. Past research has shown that word-based search tools are computationally efficient and can find some new functional similarities or dissimilarities invisible to other algorithms like FASTA. Recently, under the independent model of base composition, Wu, Burke, and Davison (1997, Biom...

Consider the problem of estimating true density, h(.) based upon a random sample X1,…, Xn. In general, h(.)is approximated using an appropriate in some sense, see below) model fƟ(x). This article using Vuong's (1989) test along with a collection of k(> 2) non-nested models constructs a set of appropriate models, say model confidence set, for unknown model h(.).Application of such confide...