PENGKLASTERAN DATA RUNTUN WAKTU BERBASIS DENSITAS PERAMALAN - , ORIEZA FEBRIANDHANI ([Yogyakarta] : Universitas Gadjah Mada, 2014)
A clustering method for time series is introduced, based on probability density of the forecast. First, autoregressive bootstrap procedure combined with nonparametric kernel estimator is applied to data to obtain estimation of the forecast densities. The estimated forecast densities are the used to construct the dissimilarity matrix and hence to perform clustering. Finally, application of this method in real dataset are discussed.