public double valueAt(double[] param) { double[] sdInv = new double[nVariables]; for (int i = 0; i < nVariables; i++) { R.setEntry(i, i, 1.0 - param[i]); sdInv[i] = 1.0 / Sinv.getEntry(i, i); } DiagonalMatrix diagSdInv = new DiagonalMatrix(sdInv); EigenDecomposition eigen = new EigenDecomposition(R); RealMatrix eigenVectors = eigen.getV().getSubMatrix(0, nVariables - 1, 0, nFactors - 1); double[] ev = new double[nFactors]; for (int i = 0; i < nFactors; i++) { ev[i] = Math.sqrt(eigen.getRealEigenvalue(i)); } DiagonalMatrix evMatrix = new DiagonalMatrix( ev); // USE Apache version of Diagonal matrix when upgrade to version 3.2 RealMatrix LAMBDA = eigenVectors.multiply(evMatrix); RealMatrix SIGMA = (LAMBDA.multiply(LAMBDA.transpose())); double value = 0.0; RealMatrix DIF = R.subtract(SIGMA); for (int i = 0; i < DIF.getRowDimension(); i++) { for (int j = 0; j < DIF.getColumnDimension(); j++) { value = DIF.getEntry(i, j); DIF.setEntry(i, j, Math.pow(value, 2)); } } RealMatrix RESID = diagSdInv.multiply(DIF).multiply(diagSdInv); double sum = 0.0; for (int i = 0; i < RESID.getRowDimension(); i++) { for (int j = 0; j < RESID.getColumnDimension(); j++) { sum += RESID.getEntry(i, j); } } return sum; }