lag.dfts

Compute a lagged version of a functional time series, shifting the time base
back by a given number of observations.

Analyze functional data and its change points. Includes
functionality to store and process data, summarize and validate assumptions,
characterize and perform inference of change points, and provide
visualizations. Data is stored as discretely collected observations without
requiring the selection of basis functions. For more details see chapter 8
of Horvath and Rice (2024) <doi:10.1007/978-3-031-51609-2>. Additional papers
are forthcoming. Focused works are also included in the documentation of
corresponding functions.

Jeremy VanderDoes

fChange

Functional Change Point Detection and Analysis

Gregory Rice

Martin Wendler

lag.dfts function

<dl><dt>x</dt>
<dd>A dfts object. See <code>dfts()</code>.</dd>
<dt>k</dt>
<dd>Integer for the number of lags (in units of observations).</dd>
<dt>...</dt>
<dd>Unused additional parameters.</dd></dl>

Arguments

Lag dfts objects — lag.dfts

<dl>

<dt>x</dt>
<dd>A dfts object. See <code>dfts()</code>.</dd>


<dt>k</dt>
<dd>Integer for the number of lags (in units of observations).</dd>


<dt>...</dt>
<dd>Unused additional parameters.</dd>

</dl>

lag.dfts: Lag dfts objects

Description

Usage

Value

Arguments

See Also

Examples