Koopmans Matthijs Using Time Series to Analyze Long Range Fractal Patterns 9781544361420

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Автор: Koopmans Matthijs
Название: Using Time Series to Analyze Long Range Fractal Patterns
ISBN: 9781544361420
Издательство: Sage Publications
Классификация:

Методы исследований: Общие положения

Социальные исследования и статистика

Политика и политический строй

Политология и политическая философия

ISBN-10: 1544361424
Обложка/Формат: Paperback
Страницы: 120
Вес: 0.14 кг.
Дата издания: 20.01.2021
Серия: Quantitative applications in the social sciences
Язык: English
Размер: 226 x 150 x 10
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Research methods: general,Social research & statistics
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Поставляется из: Англии
Описание: Using Time Series to Analyze Long Range Fractal Patterns presents methods for describing and analyzing dependency and irregularity in long time series. Irregularity refers to cycles that are similar in appearance, but unlike seasonal patterns more familiar to social scientists, repeated over a time scale that is not fixed. Until now, the application of these methods has mainly involved analysis of dynamical systems outside of the social sciences, but this volume makes it possible for social scientists to explore and document fractal patterns in dynamical social systems. Author Matthijs Koopmans concentrates on two general approaches to irregularity in long time series: autoregressive fractionally integrated moving average models, and power spectral density analysis. He demonstrates the methods through two kinds of examples: simulations that illustrate the patterns that might be encountered and serve as a benchmark for interpreting patterns in real data; and secondly social science examples such a long range data on monthly unemployment figures, daily school attendance rates; daily numbers of births to teens, and weekly survey data on political orientation. Data and R-scripts to replicate the analyses are available in an accompanying website.

Using Time Series to Analyze Long Range Fractal Patterns, Koopmans Matthijs