TemporalRegularity

TemporalRegularity

is an option for TemporalData, TimeSeries, and EventSeries that controls whether the paths are assumed to be uniformly spaced in time.

Details

  • Settings include:
  • Automaticautomatically detect regularity (default)
    Trueexplicitly assume regularity
    Falseenforce the assumption of irregularity when present

Examples

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Basic Examples  (2)

By default, regularity is determined from the data:

Explicitly assume regularity:

Treat a time series as regularly spaced:

The dates are spaced by business day:

TimeSeries does not detect regularity:

Assume the series is regular:

Scope  (1)

It is sometimes possible to achieve regularity by specifying the times as {tmin,tmax,dt}:

The dates are spaced by business day:

The paths are equivalent:

Explicitly assume regularity:

The path remains unchanged:

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

Text

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

CMS

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

APA

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

BibTeX

@misc{reference.wolfram_2024_temporalregularity, author="Wolfram Research", title="{TemporalRegularity}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/TemporalRegularity.html}", note=[Accessed: 21-November-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_temporalregularity, organization={Wolfram Research}, title={TemporalRegularity}, year={2014}, url={https://reference.wolfram.com/language/ref/TemporalRegularity.html}, note=[Accessed: 21-November-2024 ]}