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Time series analysis for the social sciences /

by Box-Steffensmeier, Janet M; Freeman, John R; Hitt, Mathew P; Pevehouse, John C. W.
Material type: materialTypeLabelBookSeries: Analytical methods for social research.Publisher: New York : Cambridge University Press, 2014Description: xv, 280 p. : ill. ; 23 cm.ISBN: 9780521871167 (hardback); 9780521691550 (paperback).Subject(s): Time-series analysis | Time-series analysis -- Mathematical modelsSummary: "Time-series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time-series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time-Series Analysis for Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time-series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse, and Matthew P. Hitt cover a wide range of topics including ARIMA models, time-series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy"-- Provided by publisher.
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Books Books Dhaka University Library
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Non Fiction 519.55 TIM (Browse shelf) 1 Available 506634
Books Books Dhaka University Library
General Stacks
Non Fiction 519.55 TIM (Browse shelf) 2 Available 506635
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519.55 TIM Time series analysis : 519.55 TIM Time series analysis : 519.55 TIM Time series analysis for the social sciences / 519.55 TIM Time series analysis for the social sciences / 519.550285 HAS Singular spectrum analysis : 519.550285 HAS Singular spectrum analysis : 519.550285 HUA Applied time series analysis and forecasting with python/

Includes bibliographical references and index.

"Time-series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time-series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time-Series Analysis for Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time-series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse, and Matthew P. Hitt cover a wide range of topics including ARIMA models, time-series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy"-- Provided by publisher.

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