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 possible non...

The problem of filtering information from large correlation matrices is of great importance in many applications. We have recently proposed the use of the Kullback–Leibler distance to measure the performance of filtering algorithms in recovering the underlying correlation matrix when the variables are described by a multivariate Gaussian distribution. Here we use the Kullback–Leibler distance t...

We define a new distance measure the resistor-average distance between two probability distributions that is closely related to the Kullback-Leibler distance. While the KullbackLeibler distance is asymmetric in the two distributions, the resistor-average distance is not. It arises from geometric considerations similar to those used to derive the Chernoff distance. Determining its relation to we...

In this paper we intend to examine the application of Kullback-Leibler, Hellinger and LINEX loss function in Dynamic Linear Model using the real price of oil for 106 years of data from 1913 to 2018 concerning the asymmetric problem in filtering and forecasting. We use DLM form of the basic Hoteling Model under Quadratic loss function, Kullback-Leibler, Hellinger and LINEX trying to address the ...

Recently Habibi et al. (2006) defined a pre-experimental criterion for the potential strength of evidence provided by an experiment, based on Kullback-Leibler distance. In this paper, we investigate the potential statistical evidence in an experiment in terms of Renyi distance and compare the potential statistical evidence in lower (upper) record values with that in the same number of ii...