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Wolfram Language & System Documentation Center
TimeSeriesThread
  • See Also
    • MovingMap
    • TimeSeriesAggregate
    • TimeSeriesResample
    • RegularlySampledQ
    • MinimumTimeIncrement
    • TimeSeriesShift
    • TimeSeriesRescale
    • TimeSeriesMap
    • TimeSeriesMapThread
    • TimeSeriesInsert
    • TimeSeriesModelFit
    • TimeSeriesWindow
    • TemporalData
    • TimeSeries
    • EventSeries
    • ResamplingMethod
  • Related Guides
    • Time Series Processing
    • See Also
      • MovingMap
      • TimeSeriesAggregate
      • TimeSeriesResample
      • RegularlySampledQ
      • MinimumTimeIncrement
      • TimeSeriesShift
      • TimeSeriesRescale
      • TimeSeriesMap
      • TimeSeriesMapThread
      • TimeSeriesInsert
      • TimeSeriesModelFit
      • TimeSeriesWindow
      • TemporalData
      • TimeSeries
      • EventSeries
      • ResamplingMethod
    • Related Guides
      • Time Series Processing

TimeSeriesThread[f,{tseries1,tseries2,…}]

combines the tseriesi using the function f.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Basic Uses  
Data Types  
Options  
Resampling Method  
Applications  
Properties & Relations  
Neat Examples  
See Also
Related Guides
History
Cite this Page
BUILT-IN SYMBOL
  • See Also
    • MovingMap
    • TimeSeriesAggregate
    • TimeSeriesResample
    • RegularlySampledQ
    • MinimumTimeIncrement
    • TimeSeriesShift
    • TimeSeriesRescale
    • TimeSeriesMap
    • TimeSeriesMapThread
    • TimeSeriesInsert
    • TimeSeriesModelFit
    • TimeSeriesWindow
    • TemporalData
    • TimeSeries
    • EventSeries
    • ResamplingMethod
  • Related Guides
    • Time Series Processing
    • See Also
      • MovingMap
      • TimeSeriesAggregate
      • TimeSeriesResample
      • RegularlySampledQ
      • MinimumTimeIncrement
      • TimeSeriesShift
      • TimeSeriesRescale
      • TimeSeriesMap
      • TimeSeriesMapThread
      • TimeSeriesInsert
      • TimeSeriesModelFit
      • TimeSeriesWindow
      • TemporalData
      • TimeSeries
      • EventSeries
      • ResamplingMethod
    • Related Guides
      • Time Series Processing

TimeSeriesThread

TimeSeriesThread[f,{tseries1,tseries2,…}]

combines the tseriesi using the function f.

Details and Options

  • TimeSeriesThread is used to combine the values of multiple time series.
  • TimeSeriesThread can be used for regularly and irregularly spaced time series.
  • The input for each of the tseriesi can be a list of time-value pairs {{t1,x1},{t2,x2},…}, a TimeSeries, EventSeries, or TemporalData.
  • All of the tseriesi must contain the same number of paths.
  • TimeSeriesThread threads pathwise for tseriesi with multiple paths.
  • The collection of paths {tseries1,tseries2,…} can equivalently be given as TemporalData[{tseries1,tseries2,…}].
  • If the times for the tseriesi are not equivalent, they are each resampled using the union of their times.
  • TimeSeriesThread takes the following option:
  • ResamplingMethodAutomaticthe method to use for resampling paths

Examples

open all close all

Basic Examples  (4)

Obtain the sum of two time series:

Combine two time series using a generic function f:

Compute the differences between two financial time series:

Find the average path:

Scope  (7)

Basic Uses  (3)

Total 10 simulated BernoulliProcess paths:

Compute a min-max envelope for some process paths:

Create a 95% confidence envelope for some process paths:

Compute a time series of means and standard deviations :

A 95% confidence interval for a normal is given :

Data Types  (4)

Obtain the sum of two time series given by time-value pairs:

Obtain the difference between two TimeSeries:

Find the standard deviation of various paths in TemporalData:

Find the maximum values between two EventSeries:

Options  (1)

Resampling Method  (1)

Combine two time series with mismatched times:

Use zero-order interpolation:

Use interpolation order 1:

Applications  (4)

Simulate a jump-diffusion process:

Generate a time series of the Sun's position and the Moon's position over a period of two months:

Define a function to compute the angular distance between two objects on a sphere:

Find the time series for the angular distance between the Sun and the Moon:

Visualize the angular distance:

Study male unemployment in France:

Unemployment rates:

Convert rates to fractions:

Male unemployment is the corresponding fraction of the male labor force:

Replace Missing[] differently for each component when combining multiple paths into a single-path vector-valued TimeSeries using TimeSeriesThread:

Properties & Relations  (1)

Compare TimeSeriesThread with TimeSeriesMap operating on a single time series:

Neat Examples  (1)

Create a lunar calendar in which the background color depends on the fraction of the Moon illumination:

Create a new event series with vector values composed of icons and fractions:

Visualize the lunar calendar:

See Also

MovingMap  TimeSeriesAggregate  TimeSeriesResample  RegularlySampledQ  MinimumTimeIncrement  TimeSeriesShift  TimeSeriesRescale  TimeSeriesMap  TimeSeriesMapThread  TimeSeriesInsert  TimeSeriesModelFit  TimeSeriesWindow  TemporalData  TimeSeries  EventSeries  ResamplingMethod

Function Repository: TimeSeriesEnsemble

Related Guides

    ▪
  • Time Series Processing

History

Introduced in 2014 (10.0)

Wolfram Research (2014), TimeSeriesThread, Wolfram Language function, https://reference.wolfram.com/language/ref/TimeSeriesThread.html.

Text

Wolfram Research (2014), TimeSeriesThread, Wolfram Language function, https://reference.wolfram.com/language/ref/TimeSeriesThread.html.

CMS

Wolfram Language. 2014. "TimeSeriesThread." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/TimeSeriesThread.html.

APA

Wolfram Language. (2014). TimeSeriesThread. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/TimeSeriesThread.html

BibTeX

@misc{reference.wolfram_2025_timeseriesthread, author="Wolfram Research", title="{TimeSeriesThread}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/TimeSeriesThread.html}", note=[Accessed: 01-March-2026]}

BibLaTeX

@online{reference.wolfram_2025_timeseriesthread, organization={Wolfram Research}, title={TimeSeriesThread}, year={2014}, url={https://reference.wolfram.com/language/ref/TimeSeriesThread.html}, note=[Accessed: 01-March-2026]}

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