Examples of RealMatrix

org.apache.commons.math.linear.RealMatrix
Interface defining a real-valued matrix with basic algebraic operations.
Matrix element indexing is 0-based -- e.g., getEntry(0, 0) returns the element in the first row, first column of the matrix.
@version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $
org.apache.commons.math3.linear.RealMatrix
Interface defining a real-valued matrix with basic algebraic operations.
Matrix element indexing is 0-based -- e.g., getEntry(0, 0) returns the element in the first row, first column of the matrix.
@version $Id: RealMatrix.java 1244107 2012-02-14 16:17:55Z erans $

Examples of org.apache.commons.math3.linear.RealMatrix

     * @return the square-root of the weight matrix.
     */
    private RealMatrix squareRoot(RealMatrix m) {
        if (m instanceof DiagonalMatrix) {
            final int dim = m.getRowDimension();
            final RealMatrix sqrtM = new DiagonalMatrix(dim);
            for (int i = 0; i < dim; i++) {
                sqrtM.setEntry(i, i, FastMath.sqrt(m.getEntry(i, i)));
            }
            return sqrtM;
        } else {
            final EigenDecomposition dec = new EigenDecomposition(m);
            return dec.getSquareRoot();

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Examples of org.apache.commons.math3.linear.RealMatrix

     * @throws NullPointerException unless method {@code newSampleData} has been
     * called beforehand.
     */
    public RealMatrix calculateHat() {
        // Create augmented identity matrix
        RealMatrix Q = qr.getQ();
        final int p = qr.getR().getColumnDimension();
        final int n = Q.getColumnDimension();
        // No try-catch or advertised NotStrictlyPositiveException - NPE above if n < 3
        Array2DRowRealMatrix augI = new Array2DRowRealMatrix(n, n);
        double[][] augIData = augI.getDataRef();
        for (int i = 0; i < n; i++) {
            for (int j =0; j < n; j++) {
                if (i == j && i < p) {
                    augIData[i][j] = 1d;
                } else {
                    augIData[i][j] = 0d;
                }
            }
        }


        // Compute and return Hat matrix
        // No DME advertised - args valid if we get here
        return Q.multiply(augI).multiply(Q.transpose());
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     * @return The beta variance-covariance matrix
     */
    @Override
    protected RealMatrix calculateBetaVariance() {
        int p = getX().getColumnDimension();
        RealMatrix Raug = qr.getR().getSubMatrix(0, p - 1 , 0, p - 1);
        RealMatrix Rinv = new LUDecomposition(Raug).getSolver().getInverse();
        return Rinv.multiply(Rinv.transpose());
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     * </pre>
     * @return beta
     */
    @Override
    protected RealVector calculateBeta() {
        RealMatrix OI = getOmegaInverse();
        RealMatrix XT = getX().transpose();
        RealMatrix XTOIX = XT.multiply(OI).multiply(getX());
        RealMatrix inverse = new LUDecomposition(XTOIX).getSolver().getInverse();
        return inverse.multiply(XT).multiply(OI).operate(getY());
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     * </pre>
     * @return The beta variance matrix
     */
    @Override
    protected RealMatrix calculateBetaVariance() {
        RealMatrix OI = getOmegaInverse();
        RealMatrix XTOIX = getX().transpose().multiply(OI).multiply(getX());
        return new LUDecomposition(XTOIX).getSolver().getInverse();
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     */
    protected RealMatrix computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected)
    throws MathIllegalArgumentException {
        int dimension = matrix.getColumnDimension();
        Variance variance = new Variance(biasCorrected);
        RealMatrix outMatrix = new BlockRealMatrix(dimension, dimension);
        for (int i = 0; i < dimension; i++) {
            for (int j = 0; j < i; j++) {
              double cov = covariance(matrix.getColumn(i), matrix.getColumn(j), biasCorrected);
              outMatrix.setEntry(i, j, cov);
              outMatrix.setEntry(j, i, cov);
            }
            outMatrix.setEntry(i, i, variance.evaluate(matrix.getColumn(i)));
        }
        return outMatrix;
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     * @return a new {@link LeastSquaresProblem} with the weights applied. The original
     *         {@code problem} is not modified.
     */
    public static LeastSquaresProblem weightMatrix(final LeastSquaresProblem problem,
                                                   final RealMatrix weights) {
        final RealMatrix weightSquareRoot = squareRoot(weights);
        return new LeastSquaresAdapter(problem) {
            @Override
            public Evaluation evaluate(final RealVector point) {
                return new DenseWeightedEvaluation(super.evaluate(point), weightSquareRoot);
            }

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Examples of org.apache.commons.math3.linear.RealMatrix

     * @return the square-root of the weight matrix.
     */
    private static RealMatrix squareRoot(final RealMatrix m) {
        if (m instanceof DiagonalMatrix) {
            final int dim = m.getRowDimension();
            final RealMatrix sqrtM = new DiagonalMatrix(dim);
            for (int i = 0; i < dim; i++) {
                sqrtM.setEntry(i, i, FastMath.sqrt(m.getEntry(i, i)));
            }
            return sqrtM;
        } else {
            final EigenDecomposition dec = new EigenDecomposition(m);
            return dec.getSquareRoot();

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Examples of org.apache.commons.math3.linear.RealMatrix

     *
     * @param matrix matrix with columns representing variables to correlate
     * @return correlation matrix
     */
    public RealMatrix computeCorrelationMatrix(final RealMatrix matrix) {
        final RealMatrix matrixCopy = rankTransform(matrix);
        return new PearsonsCorrelation().computeCorrelationMatrix(matrixCopy);
    }

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Examples of org.apache.commons.math3.linear.RealMatrix

     *
     * @param matrix matrix to transform
     * @return a rank-transformed matrix
     */
    private RealMatrix rankTransform(final RealMatrix matrix) {
        RealMatrix transformed = null;


        if (rankingAlgorithm instanceof NaturalRanking &&
                ((NaturalRanking) rankingAlgorithm).getNanStrategy() == NaNStrategy.REMOVED) {
            final Set<Integer> nanPositions = new HashSet<Integer>();
            for (int i = 0; i < matrix.getColumnDimension(); i++) {
                nanPositions.addAll(getNaNPositions(matrix.getColumn(i)));
            }


            // if we have found NaN values, we have to update the matrix size
            if (!nanPositions.isEmpty()) {
                transformed = new BlockRealMatrix(matrix.getRowDimension() - nanPositions.size(),
                                                  matrix.getColumnDimension());
                for (int i = 0; i < transformed.getColumnDimension(); i++) {
                    transformed.setColumn(i, removeValues(matrix.getColumn(i), nanPositions));
                }
            }
        }


        if (transformed == null) {
            transformed = matrix.copy();
        }


        for (int i = 0; i < transformed.getColumnDimension(); i++) {
            transformed.setColumn(i, rankingAlgorithm.rank(transformed.getColumn(i)));
        }


        return transformed;
    }

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