This work develops a statistical model to assess the frost risk in Rafsanjan, one of the largest pistachio production regions in the world. These models can be used to estimate the probability that a frost happens in a given time-period during the year; a frost happens after 10 warm days in the growing season. These probability estimates then can be used for: (1) assessing the agroclimate risk ...

In this work, we present a methodology for spike enhancement in electroencephalographic (EEG) recordings. Our approach takes advantage of the non-stationarity nature of the EEG signal using a time-varying autoregressive model. The time-varying coefficients of autoregressive model are estimated using the Kalman filter. The results show considerable improvement in signal-to-noise ratio and signif...

Spatially Varying Autoregressive Processes Aline A. Nobre, Bruno Sansó and Alexandra M. Schmidt Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro-RJ CEP:21.045-900, Brazil Department of Applied Mathematics and Statistics, University of California at Santa Cruz, Santa Cruz, CA 95064 Instituto de Matemática, Universidade Federal do Rio de Janeiro, Rio de Janeiro-RJ CEP:21.945-...

This paper investigates the relationship between inflation and growth uncertainty in Iran for the period of 1988-2008 by using quarterly data. We employ Generalized Autoregressive Conditional Heteroscedasticity in Mean (GARCH-M) model to estimate time-varying conditional residual variance of growth, as a standard measures of growth uncertainty. The empirical evidence shows that growth uncertain...