The article entitled "Tests for comparing time series of unequal lengths" by Jorge Caiado, Nuno Crato and Daniel Peña (Universidad Carlos III de Madrid, Spain) has been accepted for publication in the ISI international journal "Journal of Statistical Computation and Simulation".
In this article, the authors propose two statistical tests to compare independent time series with an unequal number of observations. The first test is based on the distance between the ordinates of the periodogram and uses the periodogram interpolation methodology introduced by Caiado, Crato and Peña (2009, Communication in Statistics: Simulation and Computation 38, 527-540) to classify and group time series. The second is a parametric test based on the distance between the parameter estimates of an autoregressive model and moving averages. These tests are compared with a third test, based on the pooled spectra, through a Monte Carlo simulation study.
Jorge Caiado (PhD) is a researcher at the Center for Mathematics Applied to Economic Forecasting and Decision (CEMAPRE/ISEG).
Nuno Crato (PhD) is a full professor at ISEG and a researcher at the Center for Mathematics Applied to Economic Forecasting and Decision (CEMAPRE).
