Time series analysis / / by Mark Pickup ; edited by Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A. Williams.

Time series data are chronological sequences of observations produced by regularly and repeatedly measuring some characteristic or characteristics of the same case over time (e.g., aggregate support for the government in a country, the crime rate in a city). Time series analysis is the application o...

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Place / Publishing House:London : : SAGE Publications Ltd.,, 2020.
Year of Publication:2020
Language:English
Physical Description:1 online resource :; illustrations
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Summary:Time series data are chronological sequences of observations produced by regularly and repeatedly measuring some characteristic or characteristics of the same case over time (e.g., aggregate support for the government in a country, the crime rate in a city). Time series analysis is the application of statistical models to time series data. This entry defines time series analysis and distinguishes time series data from other forms of data. It defines important time series notation and terminology. It provides a discussion of the challenges of time series analysis and of key time series fundamentals: autoregression, autocorrelation, serial correlation, stationarity, exogeneity, weak dependence, trending, seasonality, structural breaks, and stability.
Bibliography:Includes bibliographical references and index.
ISBN:1529748739
Hierarchical level:Monograph
Statement of Responsibility: by Mark Pickup ; edited by Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A. Williams.