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2009-09-03T14:29:57.727
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Have you tried creating a <a href="http://commons.apache.org/math/userguide/stat.html#a1.7_Covariance_and_correlation" rel="nofollow noreferrer">Covariance matrix directly from your data</a>? <pre><code>new Covariance().computeCovarianceMatrix(data) </code></pre> Using the information in the comment, we know that there are 3 independent, 1 dependent variables and 200 samples. That implies that you will have a data array with 4 columns and 200 rows. The end result will look something like this (typing everything out explicitly in order to try to explain what I mean): <pre><code>double [] data = new double [4][]; data[0] = new double[]{y[0], x[0][0], x[1][0], x[2][0]}; data[1] = new double[]{y[1], x[0][1], x[1][1], x[2][1]}; data[2] = new double[]{y[2], x[0][2], x[1][2], x[2][2]}; // ... etc. data[199] = new double[]{y[199], x[0][199], x[1][199], x[2][199]}; Covariance covariance = new Covariance().computeCovarianceMatrix(data); double [][] omega = covariance.getCovarianceMatrix().getData(); </code></pre> Then, <a href="http://commons.apache.org/math/userguide/stat.html#a1.5_Multiple_linear_regression" rel="nofollow noreferrer">when you're doing your actual regression</a>, you have your covariance matrix: <pre><code>MultipleLinearRegression regression = new GLSMultipleLinearRegression(); // Assumes you put your independent variables in x and dependent in y // Also assumes that you made your covariance matrix as shown above regression.addData(y, x, omega); // we do need covariance </code></pre>
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1. POMultiple Linear Regression
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1. COYes i tried doing that - my problem is that i have 200 items for each X so it is not a square matrix and GLS is complaining that org.apache.commons.math.MathRuntimeException$4: dimension mismatch 200 != 3 Sorry I should have mentioned that in the problem statement i will edit it now
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2. CO@Bharani, updated the answer to try to address your comment.
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