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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Classification and clustering of time series

Classification and clustering of time series

Caiado, Jorge

Paperback

Probability & Statistics

ISBN10: 3838341813
ISBN13: 9783838341811
Publisher: Lap Lambert Academic Pub
Published: Jun 24 2010
Pages: 208
Weight: 0.69
Height: 0.48 Width: 6.00 Depth: 9.00
Language: English
Classification and clustering of time series is becoming an important area of research in several fields, such as economics, marketing, business, finance, medicine, biology, physics, psychology, zoology, and many others. For example, in economics we may be interested in classifying the economic situation of a country by looking at some time series indicators, such as Gross National Product, disposable income, unemployment rate or inflation rate. In this book, we propose new measures of distance between time series based on the autocorrelations, partial and inverse autocorrelations, and periodogram ordinates. The use of both hierarchical and nonhierarchical clustering algorithms is considered. We also introduce time and frequency domain based metrics for classification of time series with unequal lengths. As economic applications, we present two illustrative examples. The first uses economic time series data to identify similarities among industrial production series in the United States. The second applies the interpolated periodogram based method for classifying time series with unequal lengths of industrialized countries.

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