Classification and clustering of time series (Paperback)

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.

General

Imprint:	Lap Lambert Academic Publishing
Country of origin:	Germany
Release date:	June 2010
First published:	June 2010
Authors:	Jorge Caiado
Dimensions:	229 x 152 x 12mm (L x W x T)
Format:	Paperback - Trade
Pages:	208
ISBN-13:	978-3-8383-4181-1
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	3-8383-4181-3
Barcode:	9783838341811

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!