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http://dx.doi.org/10.5351/KJAS.2019.32.1.149

Nonparametric clustering of functional time series electricity consumption data  

Kim, Jaehee (Department of Statistics, Duksung Women's University)
Publication Information
The Korean Journal of Applied Statistics / v.32, no.1, 2019 , pp. 149-160 More about this Journal
Abstract
The electricity consumption time series data of 'A' University from July 2016 to June 2017 is analyzed via nonparametric functional data clustering since the time series data can be regarded as realization of continuous functions with dependency structure. We use a Bouveyron and Jacques (Advances in Data Analysis and Classification, 5, 4, 281-300, 2011) method based on model-based functional clustering with an FEM algorithm that assumes a Gaussian distribution on functional principal components. Clusterwise analysis is provided with cluster mean functions, densities and cluster profiles.
Keywords
ARIMA; electricity consumption; functional clustering; functional data analysis;
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