na.interpolation

na.interpolation is replaced by <code>na_interpolation</code>.
The functionality stays the same. The new name better fits modern R code
style guidelines (which prefer _ over . in function names).

internal

Imputation (replacement) of missing values
in univariate time series.
Offers several imputation functions
and missing data plots.
Available imputation algorithms include:
'Mean', 'LOCF', 'Interpolation',
'Moving Average', 'Seasonal Decomposition',
'Kalman Smoothing on Structural Time Series models',
'Kalman Smoothing on ARIMA models'. Published in Moritz and Bartz-Beielstein (2017)
<doi:10.32614/RJ-2017-009>.

Steffen Moritz

imputeTS

Time Series Missing Value Imputation

Sebastian Gatscha

Earo Wang

Ron Hause

na.interpolation function

<dl><dt>x</dt>
<dd>Numeric Vector (<code><a href="/link/vector?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::vector">vector</a></code>) or Time Series (<code><a href="/link/ts?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::ts">ts</a></code>)
object in which missing values shall be replaced</dd>
<dt>option</dt>
<dd>Algorithm to be used. Accepts the following input:<ul>
<li>"linear" - for linear interpolation using <a href="/link/approx?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::approx">approx</a> (default choice)</li>
<li>"spline" - for spline interpolation using <a href="/link/spline?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::spline">spline</a></li>
<li>"stine" - for Stineman interpolation using stinterp</li>
</ul></dd>
<dt>maxgap</dt>
<dd>Maximum number of successive NAs to still perform imputation on.
Default setting is to replace all NAs without restrictions. With this
option set, consecutive NAs runs, that are longer than 'maxgap' will
be left NA. This option mostly makes sense if you want to
treat long runs of NA afterwards separately.</dd>
<dt>...</dt>
<dd>Additional parameters to be passed through to <a href="/link/approx?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::approx">approx</a> or
<a href="/link/spline?package=imputeTS&version=3.3" data-mini-rdoc="imputeTS::spline">spline</a> interpolation functions</dd></dl>

Arguments

Deprecated use na_interpolation instead. — na.interpolation

<dl>

<dt>x</dt>
<dd>Numeric Vector (<code><a href='https://rdrr.io/r/base/vector.html'>vector</a></code>) or Time Series (<code><a href='https://rdrr.io/r/stats/ts.html'>ts</a></code>)
object in which missing values shall be replaced</dd>


<dt>option</dt>
<dd>Algorithm to be used. Accepts the following input:<ul>
<li>"linear" - for linear interpolation using <a href='https://rdrr.io/r/stats/approxfun.html'>approx</a> (default choice)</li>
<li>"spline" - for spline interpolation using <a href='https://rdrr.io/r/stats/splinefun.html'>spline</a></li>
<li>"stine" - for Stineman interpolation using stinterp</li>
</ul></dd>


<dt>maxgap</dt>
<dd>Maximum number of successive NAs to still perform imputation on.
Default setting is to replace all NAs without restrictions. With this
option set, consecutive NAs runs, that are longer than 'maxgap' will
be left NA. This option mostly makes sense if you want to
treat long runs of NA afterwards separately.</dd>


<dt>...</dt>
<dd>Additional parameters to be passed through to <a href='https://rdrr.io/r/stats/approxfun.html'>approx</a> or
<a href='https://rdrr.io/r/stats/splinefun.html'>spline</a> interpolation functions</dd>

</dl>

na.interpolation: Deprecated use `na_interpolation` instead.

Description

Usage

Arguments