Examples of org.apache.commons.math3.analysis.differentiation.DerivativeStructure.multiply()

org.apache.commons.math3.analysis.differentiation.DerivativeStructure.multiply()
{@inheritDoc}

         * hPowers[m-1] = h^m
         */
        final BigFraction[] hPowers = new BigFraction[m];
        hPowers[0] = h;
        for (int i = 1; i < m; ++i) {
            hPowers[i] = h.multiply(hPowers[i - 1]);
        }


        /*
         * First column and last row has special values (each other reversed).
         */

View Full Code Here

        /*
         * [1] states: "For 1/2 < h < 1 the bottom left element of the matrix should be (1 - 2*h^m +
         * (2h - 1)^m )/m!" Since 0 <= h < 1, then if h > 1/2 is sufficient to check:
         */
        if (h.compareTo(BigFraction.ONE_HALF) == 1) {
            Hdata[m - 1][0] = Hdata[m - 1][0].add(h.multiply(2).subtract(1).pow(m));
        }


        /*
         * Aside from the first column and last row, the (i, j)-th element is 1/(i - j + 1)! if i -
         * j + 1 >= 0, else 0. 1's and 0's are already put, so only division with (i - j + 1)! is

View Full Code Here

        final FieldMatrix<BigFraction> Hpower = H.power(n);


        BigFraction pFrac = Hpower.getEntry(k - 1, k - 1);


        for (int i = 1; i <= n; ++i) {
            pFrac = pFrac.multiply(i).divide(n);
        }


        /*
         * BigFraction.doubleValue converts numerator to double and the
         * denominator to double and divides afterwards. That gives NaN quite

View Full Code Here

         * hPowers[0] = h^1 ... hPowers[m-1] = h^m
         */
        final BigFraction[] hPowers = new BigFraction[m];
        hPowers[0] = h;
        for (int i = 1; i < m; ++i) {
            hPowers[i] = h.multiply(hPowers[i - 1]);
        }


        /*
         * First column and last row has special values (each other reversed).
         */

View Full Code Here

         * [1] states: "For 1/2 < h < 1 the bottom left element of the matrix
         * should be (1 - 2*h^m + (2h - 1)^m )/m!" Since 0 <= h < 1, then if h >
         * 1/2 is sufficient to check:
         */
        if (h.compareTo(BigFraction.ONE_HALF) == 1) {
            Hdata[m - 1][0] = Hdata[m - 1][0].add(h.multiply(2).subtract(1).pow(m));
        }


        /*
         * Aside from the first column and last row, the (i, j)-th element is
         * 1/(i - j + 1)! if i - j + 1 >= 0, else 0. 1's and 0's are already

View Full Code Here


            BigFraction ck     = coefficients.get(startK);
            BigFraction ckm1   = coefficients.get(startKm1);


            // degree 0 coefficient
            coefficients.add(ck.multiply(ai[0]).subtract(ckm1.multiply(ai[2])));


            // degree 1 to degree k-1 coefficients
            for (int i = 1; i < k; ++i) {
                final BigFraction ckPrev = ck;
                ck     = coefficients.get(startK + i);

View Full Code Here

            // degree 1 to degree k-1 coefficients
            for (int i = 1; i < k; ++i) {
                final BigFraction ckPrev = ck;
                ck     = coefficients.get(startK + i);
                ckm1   = coefficients.get(startKm1 + i);
                coefficients.add(ck.multiply(ai[0]).add(ckPrev.multiply(ai[1])).subtract(ckm1.multiply(ai[2])));
            }


            // degree k coefficient
            final BigFraction ckPrev = ck;
            ck = coefficients.get(startK + k);

View Full Code Here

            }


            // degree k coefficient
            final BigFraction ckPrev = ck;
            ck = coefficients.get(startK + k);
            coefficients.add(ck.multiply(ai[0]).add(ckPrev.multiply(ai[1])));


            // degree k+1 coefficient
            coefficients.add(ck.multiply(ai[1]));


        }

View Full Code Here

            for (int i = 0; i < n; i++) {
                for (int j = 0; j < k; j++) {
                    final RealMatrix vec
                        = new Array2DRowRealMatrix(MathArrays.ebeSubtract(data[i], newMeans[j]));
                    final RealMatrix dataCov
                        = vec.multiply(vec.transpose()).scalarMultiply(gamma[i][j]);
                    newCovMats[j] = newCovMats[j].add(dataCov);
                }
            }


            // Converting to arrays for use by fitted model

View Full Code Here

            for (int col = 0; col < dim; col++) {
                tmpMatrix.multiplyEntry(row, col, factor);
            }
        }


        samplingMatrix = covMatEigenvectors.multiply(tmpMatrix);
    }


    /**
     * Gets the mean vector.
     *

View Full Code Here

0 1 2 3 4 5 6 7 8 9

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.