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Time series is a sequence of data points, measured typically at successive times spaced at uniform time intervals.
A time series is an ordered finite set (a sequence) of data points, typically consisting of measurements observed successively over a time interval.
We performed a time series analysis, modelling a sequence of data points (dependent variable) measured at successive time instants, spaced at uniform time intervals.
The sample entropy (SampEn) in a set of data points is the negative natural logarithm of the conditional probability that a sequence of data points with length N, having repeated itself within a tolerance t for M points, will also repeat itself for M + 1 points, without allowing self-matches [ 11].
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Modelling the risk of a single time series that is, one variable over a single sequence of data points—is relatively simple.
Each sequence of data points can be thought of as an n-dimensional vector, usually written as a column vector.
They then used the movements of the reflectors to analyse who was affecting whom.To do this, Dr D'Ausilio employed a mathematical trick called the Granger causality test, which makes it possible to determine how one sequence of data points affects another.
RQA quantifies, for instance, whether a data point recurs at another point in time, or whether a sequence of recurring data points forms a recurring pattern of (multiple) neighboring data points in the reconstructed phase space.
Primarily, it is designed to analyze sequences of data points with a demonstration of data values at consistent times.
A discrete cosine transform (DCT) expresses a sequence of finite data points in terms of a sum of cosine functions oscillating at different frequencies.
The non-parametric smoother allows estimation of an average value for IR in sequences of small subsets, each covering a portion of data points.
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