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Classification and clustering of time series by Jorge Caiado (Paperback, 2010)

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About this product

Product Information

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.

Product Identifiers

PublisherLAP

ISBN-139783838341811

eBay Product ID (ePID)92993062

Product Key Features

Number of Pages208 Pages

Publication NameClassification and Clustering of Time Series

LanguageEnglish

SubjectMathematics

Publication Year2010

TypeTextbook

AuthorJorge Caiado

FormatPaperback

Dimensions

Item Height229 mm

Item Weight313 g

Item Width152 mm

Additional Product Features

Country/Region of ManufactureGermany

Title_AuthorJorge Caiado