Time series clustering based on forecast densities

  • A. M. Alonsoa, J. R. Berrenderob, +1 author A. Justelb
  • Published 2005
A new clustering method for time series is proposed, based on the full probability density of the forecasts. First, a resampling method combined with a nonparametric kernel estimator provides estimates of the forecast densities. A measure of discrepancy is then defined between these estimates and the resulting dissimilarity matrix is used to carry out the… (More)