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Changing doc to reflect revised constructor for SimpleRegression 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1167460 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Greg Sterijevski 2011-09-10 05:20:56 +00:00
parent 99458101a5
commit 25acfb6505
1 changed files with 33 additions and 2 deletions
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35
src/site/xdoc/userguide/stat.xml
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@ -365,6 +365,10 @@ System.out.println(f.getCumPct("z")); // displays 1
<code> y = intercept + slope * x </code>
</p>
<p>
or
<p>
<code> y = slope * x </code>
</p>
Standard errors for <code>intercept</code> and <code>slope</code> are
available as well as ANOVA, r-square and Pearson's r statistics.
</p>
@ -408,7 +412,6 @@ System.out.println(f.getCumPct("z")); // displays 1
Here are some examples.
<dl>
<dt>Estimate a model based on observations added one at a time</dt>
<br></br>
<dd>Instantiate a regression instance and add data points
<source>
regression = new SimpleRegression();
@ -445,8 +448,8 @@ System.out.println(regression.predict(1.5d)
More data points can be added and subsequent getXxx calls will incorporate
additional data in statistics.
</dd>
<br></br>
<dt>Estimate a model from a double[][] array of data points</dt>
<br></br>
<dd>Instantiate a regression object and load dataset
<source>
double[][] data = { { 1, 3 }, {2, 5 }, {3, 7 }, {4, 14 }, {5, 11 }};
@ -468,6 +471,34 @@ System.out.println(regression.getSlopeStdErr());
More data points -- even another double[][] array -- can be added and subsequent
getXxx calls will incorporate additional data in statistics.
</dd>
<br></br>
<dt>Estimate a model from a double[][] array of data points, <em>excluding</em> the intercept</dt>
<dd>Instantiate a regression object and load dataset
<source>
double[][] data = { { 1, 3 }, {2, 5 }, {3, 7 }, {4, 14 }, {5, 11 }};
SimpleRegression regression = new SimpleRegression(false);
//the argument, false, tells the class not to include a constant
regression.addData(data);
</source>
</dd>
<dd>Estimate regression model based on data
<source>
System.out.println(regression.getIntercept());
// displays intercept of regression line, since we have constrained the constant, 0.0 is returned
System.out.println(regression.getSlope());
// displays slope of regression line
System.out.println(regression.getSlopeStdErr());
// displays slope standard error
System.out.println(regression.getInterceptStdErr() );
// will return Double.NaN, since we constrained the parameter to zero
</source>
Caution must be exercised when interpreting the slope when no constant is being estimated. The slope
may be biased.
</dd>
</dl>
</p>
</subsection>