期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 51, 期 2, 页码 762-776出版社
ELSEVIER
DOI: 10.1016/j.csda.2006.04.035
关键词
bootstrap; cluster analysis; L-2-distance; Kyoto protocol; nonparametric density estimation; prediction
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 required cluster analysis. Applications of this method to both simulated and real life data sets are discussed. (c) 2006 Elsevier B.V. All rights reserved.
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