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<table width="100%" summary="page for heart"><tr><td>heart</td><td align="right">R Documentation</td></tr></table>

<h2>Heart Catherization Data</h2>

<h3>Description</h3>


<p>This data set was analyzed by Weisberg (1980) and Chambers et
al. (1983).  A catheter is passed into a major vein or artery at the
femoral region and moved into the heart.  The proper length of the
introduced catheter has to be guessed by the physician. The aim of the
data set is to describe the relation between the catheter length and
the patient's height (X1) and weight (X2).
</p>
<p>This data sets is used to demonstrate the effects caused by collinearity.
The correlation between height and weight is so high that either
variable almost completely determines the other.
</p>


<h3>Usage</h3>

<pre>
data(heart)



</pre>


<h3>Format</h3>


<p>A data frame with 12 observations on the following 3 variables.
</p>

<dl>
<dt><code>height</code></dt><dd><p>Patient's height in inches</p>
</dd>
<dt><code>weight</code></dt><dd><p>Patient's weights in pounds</p>
</dd>
<dt><code>clength</code></dt><dd><p>Y: Catheter Length (in centimeters)</p>
</dd>
</dl>



<h3>Note</h3>

<p>There are other <code>heart</code> datasets in other <font face="Courier New,Courier" color="#666666"><b>R</b></font> packages,
notably <span class="pkg">survival</span>, hence considering using
<code>package = "robustbase"</code>, see examples.
</p>


<h3>Source</h3>


<p>Weisberg (1980)
</p>
<p>Chambers et al. (1983)
</p>
<p>P. J. Rousseeuw and A. M. Leroy (1987)
<EM>Robust Regression and Outlier Detection</EM>;
Wiley, p.103, table 13.
</p>


<h3>Examples</h3>

<pre>
data(heart, package="robustbase")
heart.x &lt;- data.matrix(heart[, 1:2]) # the X-variables
plot(heart.x)
covMcd(heart.x)
summary( lm.heart &lt;-     lm(clength ~ . , data = heart))
summary(lts.heart &lt;- ltsReg(clength ~ . , data = heart))
</pre>


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