Rescaled range analysis is a statistical technique used to detect and quantify long-range dependence and persistence in time series data. It is particularly useful in fields like finance and hydrology to identify trends and cycles that are not apparent through traditional statistical methods.

Rescaled Range Analysis

Rescaled range analysis

statistical technique

Long-range dependence, also known as long memory or long-range persistence, refers to the phenomenon where correlations between elements of a time series decay more slowly than an exponential decay, typically following a power law. This characteristic implies that past values have a significant influence on future values over long time intervals, impacting fields such as finance, hydrology, and network traffic analysis.

long-range dependence

persistence in time series data

fields like finance

Hydrology is the scientific study of the movement, distribution, and quality of water on Earth, encompassing both the water cycle and water resources. It plays a critical role in understanding environmental processes, managing water resources, and mitigating the impacts of natural disasters like floods and droughts.

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