What techniques can i use for automatic periodicity detection specifically in noisy "multi-variate" time series data?
By multi-variate time series, i mean that i have multiple (>1000) variables measured at each time point and i am looking for a way to find the period in this data. The data may have an underlying trend (unknown) and is often corrupted by noise.
I've found several possible ways of doing this in univariate time series data and one way is as follows:
I am also interested in ways to:
Detect whether or not a time-series is periodic (ex: may be a statistical test)
Measure/Quantify its periodicity level/degree between say [0,1] since its very likely that the time-series is distorted/corrupted by noise.
If it is periodic, i would like to find its period