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The comment by Stefan R answers the question. As others have pointed out, the only time series package is a third-party package and it is not compatible with Mathematica 9 or later. Mathematica 9 has built-in support for time series via TemporalData, and this is greatly expanded on in Mathematica 10.


The Dickey-Fuller and the Phillips-Perron tests are now available using UnitRootTest, introduced in Mathematica 9.


This is the purpose of the TemporalRegularity option. TemporalRegularity is an option for TemporalData, TimeSeries, and EventSeries that controls whether the paths are assumed to be uniformly spaced in time. When setting this option, the dates themselves are ignored and a standard index {0,1,...,n} is used in its place, allowing for non-uniform ...


I could not find a way to prevent the addition, so you might be left with cleaning up after the fact. Depending on which side you control, you could either add the missing bits, or remove the excess. If you want to add the missing parts: datComplete = {DateObject[{2007, 1, #}, TimeObject[{0, 0, 0}], TimeZone -> $TimeZone], #} & /...


For version 9, there is TemporalData`EnsembleMovingMap: x = Get@""; time = Table[t/60, {t, 1, Length@x}] // N; td = TemporalData[Transpose[{time, #}] & /@ Transpose[x]]; ListPlot[TemporalData[{td, TemporalData`EnsembleMovingMap[Mean, td, 180]}], Joined -> True, Frame -> True] If needed, wrap the moving map ...


Following the hint from xslittlegrass one can do also the following: time = Table[t/60, {t, 1, number}] // N; x << ""; nPoints = 180; (* Moving Average over 180 points*) xaverage = MovingAverage[#, nPoints] & /@ Transpose[x]; naverage = Length@xaverage[[1, All]]; (*is same for each averaged list*) Show[ ...

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