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Time series are data observed over time (either in continuous time or at discrete time periods).
2
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0
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Testing for white noise for non stationary time series
I could not find a question where testing for white noise for non strick stationary non parametric time series is adressed. Per definition white noise is stationary. But finding a series that is stati …
2
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time-series analysis Vs statistical signal processing
It all boils down on how would you want to process a time series as to breakdown its components as to use these for later prediction or classification.
For one ARIMA is a parametric method (assumpt …
1
vote
1
answer
161
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Autocorrelation for regression
I am attempting to use a significant autocorrelation (where it lies outside a 95% interval around 0) indicating periodicity of a signal and use it as predictive variable in a regression.
If, for exam …
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Weak stationarity and ARMA-ARCH/GARCH models?
Strict stationarity is the strongest form of stationarity. It means that the joint statistical distribution of any collection of the time series variates never depends on time. So, the mean, variance …
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Statistical comparison of two signals
There is no one single algorithm that will yield what you want.
If your desire is to compare two signals then from the signal procesing point of view you can do the following.
If the signal is sta …
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How to determine if two time series are significantly related to each other
Cross recurrence plot (CRP) will be the equivalent of cross phase analysis in wavelets. CRP is a graph which shows all those times at which a state in one dynamical system occurs simultaneously in a s …