Examples of org.apache.commons.math3.random.JDKRandomGenerator.nextGaussian()

Class org.apache.commons.math3.random.JDKRandomGenerator

Examples of org.apache.commons.math3.random.JDKRandomGenerator.nextGaussian()

org.apache.commons.math3.random.JDKRandomGenerator.nextGaussian()
Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence. @return the next pseudorandom, Gaussian ("normally") distributeddouble value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence


            // x = A * x + B * u + pNoise
            x = A.operate(x).add(B.operate(u)).add(pNoise);


            // Simulate the measurement
            mNoise.setEntry(0, measurementNoise * rand.nextGaussian());


            // z = H * x + m_noise
            RealVector z = H.operate(x).add(mNoise);


            filter.correct(z);

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        // Columns are draws on N(0, sigma[col])
        final int numSeeds = 1000;
        RealMatrix errorSeeds = MatrixUtils.createRealMatrix(numSeeds, nObs);
        for (int i = 0; i < numSeeds; i++) {
            for (int j = 0; j < nObs; j++) {
                errorSeeds.setEntry(i, j, rg.nextGaussian() * sigma[j]);
            }
        }
        
        // Get covariance matrix for columns
        RealMatrix cov = (new Covariance(errorSeeds)).getCovarianceMatrix();

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        // Columns are draws on N(0, sigma[col])
        final int numSeeds = 1000;
        RealMatrix errorSeeds = MatrixUtils.createRealMatrix(numSeeds, nObs);
        for (int i = 0; i < numSeeds; i++) {
            for (int j = 0; j < nObs; j++) {
                errorSeeds.setEntry(i, j, rg.nextGaussian() * sigma[j]);
            }
        }
        
        // Get covariance matrix for columns
        RealMatrix cov = (new Covariance(errorSeeds)).getCovarianceMatrix();

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