Much current research in functional MRI employs multivariate machine learning approaches (e.g., support vector machines) to detect fine-scale spatial patterns from the temporal fluctuations of the neural signal. The aim of many studies is not classification, however, but investigation of...

In this paper we show how the latent Markov model can be used to define different conditions in the stock market, called market- regimes. Changes in regimes can be used to detect financial crises, pinpoint the end of a crisis and predict future developments in the stock market, to some degree....

The potential offered by the increasing availability of micro-geographic data is tremendous and still largely not exploited. In this paper, we propose a new methodology to study the spatial dynamics of firm demography making use of such rich source of information. Exploiting the techniques of...