The most common cause of violation of stationarity are trends in mean, which can be due either to the presence of a unit root or of a deterministic trend.
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The authors further argue that rather than using Box Jenkins, it is better to use state space methods, as stationarity of the time series is then not required.
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:The proposed solution in the geostatistical formalism consists in assuming various degrees of stationarity in the random function, in order to make possible the inference of some statistic values.
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Stationarity is the property of a random process which guarantees that its statistical properties, such as the mean value, its moments and variance, will not change over time.
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:* Caers also use the assumption of stationarity in the context of multiple-point geostatistics, where higher n-point statistics are assumed to be stationary in the spatial domain.
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This focus on the vis viva by the continental physicists eventually led to the discovery of stationarity principles governing mechanics, such as the D'Alembert's principle and Hamiltonian formulations of mechanics.
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These two models can be combined into an autoregressive-moving average ( ARMA ) model, or an autoregressive-integrated-moving average ( ARIMA ) model if non-stationarity is involved.
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The hypothesis of stationarity related to the second moment is defined in the following way : the correlation between two random variables solely depends on the spatial distance between them, and is independent of their location:
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The final assumption about stationarity is difficult to test from data for a single site because of the large uncertainties in even the longest flood records and that managing flood risks in the future will become even more difficult.
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Any time-invariant operations also preserves AEP, stationarity and ergodicity and we may easily turn a stationary process to non-stationary without losing AEP by nulling out a finite number of time samples in the process.
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