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April 19, 201690 citations

The Effects of the Irregular Sample and Missing Data in Time Series Analysis

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DKDavid KreindlerCLCharles J. Lumsden

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Abstract

Humanself-reporttimeseriesdataaretypicallymarkedbyirregularitiesin samplingrates;furthermore,theseirregularitiesaretypicallynaturaloutcomesofthedatagenerationprocess.Relativelylittlehasbeenpublished toassisttheanalysisofirregularlysampleddata.Wereporttheresultsof aseriesofcomputationalexperimentsonsyntheticdatasetsdesignedto assesstheutilityoftechniquesforhandlingirregulartimeseriesdata.The behaviorofaconservativequasiperiodic,adissipativechaotic,andaselforganizedcriticaldynamicsweresampledregularlyintime,andtheregular samplingwasdisruptedbydatapointremovalorbystochasticshiftsintime. Missingdatasegmentswerethenpatchedbymeansofsegmentconcatenation,bysegment‡llingwithaveragedatavalues,orbylocalinterpolationin phasespace.Wecomparedresultsofnonlinearanalyticaltools,suchasautocorrelationsandcorrelationdimensions,usingcompleteandpatchedsets,as wellaspowerspectrawithLombperiodogramsofthedecimatedsets.Local interpolationinphasespacewasparticularlysuccessfulatpreservingkeyCONTENTSMethods ................................................................................................................ 137 Time Series Length ......................................................................................... 137 Dynamics ......................................................................................................... 138 Patching the Decimated Time Series ........................................................... 141 Time Series Analysis ...................................................................................... 142Results ................................................................................................................... 144 Effects of Missing Points and Temporal Inaccuracy ................................. 144 Correlation Dimension .................................................................................. 147Discussion ............................................................................................................ 153 Acknowledgments .............................................................................................. 155 References ............................................................................................................. 155featuresoftheoriginaldata,butrequiredpotentiallyimpracticalquantities ofintactdataasaprimer.Whiletheotherpatchingmethodsarenotlimited bytheneedforintactdata,theydistortresultsrelativetotheintactseries. Weconcludethatirregularlysampleddatasetswithasmuchas15%missing datacanpotentiallyberesampledorrepairedforanalysiswithtechniques that assume regular sampling without introducing substantial errors.

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Kreindler et al. (2016) studied this question.

synapsesocial.com/papers/6a1d1a4b43708a372d5dbdfehttps://doi.org/10.1201/9781439820025-9
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