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<meta property="og:description" content="Monthly totals of international airline passengers, 1949 to 1960.
This time series provides the truth for the missing values of the tsAirgap time series. Thus it is identical
to the tsAirgap time series except that no value is missing." />
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    <h1>Time series of monthly airline passengers (complete)</h1>
    <small class="dont-index">Source: <a href='https://github.com/SteffenMoritz/imputeTS/blob/master/R/tsAirgapComplete.R'><code>R/tsAirgapComplete.R</code></a></small>
    <div class="hidden name"><code>tsAirgapComplete.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Monthly totals of international airline passengers, 1949 to 1960.
This time series provides the truth for the missing values of the <code><a href='tsAirgap.html'>tsAirgap</a></code> time series. Thus it is identical
to the tsAirgap time series except that no value is missing.</p>
    </div>

    <pre class="usage"><span class='va'>tsAirgapComplete</span></pre>


    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>

    <p>Time Series (<code><a href='https://rdrr.io/r/stats/ts.html'>ts</a></code>) with 144 rows.</p>
    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>

    <p><cite>Box, G. E. P., Jenkins, G. M., Reinsel, G. C. and Ljung, G. M. (2015). Time series analysis: forecasting and control. Fifth Edition. John Wiley \&amp; Sons.</cite></p>
    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>

    <p>The dataset originates from Box &amp; Jenkins (see citation) and is a commonly used example in
time series analysis literature.</p>
<p>It characteristics (strong trend, strong seasonal behavior) make it also a great
example for time series imputation.
Thus the version with inserted NA gaps was created under the name tsAirgap.</p>
<p>In order to use this series for comparing imputation algorithm results,
there are two time series provided. One series without missing values, which can
be used as ground truth. Another series with NAs, on which the imputation
algorithms can be applied.</p>
<p>There are the two time series:</p><ul>
<li><p>tsAirgap - The time series with NAs.</p></li>
<li><p>tsAirgapComplete - Time series without NAs.</p></li>
</ul>

    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>

    <div class='dont-index'><p><code><a href='tsHeating.html'>tsHeating</a></code>, <code><a href='tsNH4.html'>tsNH4</a></code></p></div>

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