protected void compute() {
nny = (int) ni[0].parseInput();
df.writeLine("Number of events is: n = " + nny);
y = DatanRandom.standardNormal(nny);
out(y);
mllg = new MinLogLikeGauss(y);
x0 = new DatanVector(2);
x0.setElement(0, 1.);
x0.setElement(1, 2.);
MinSim ms = new MinSim(x0, mllg);
x = ms.getMinPosition();
fcont = ms.getMinimum();
df.writeLine("Minimization with MinSim yields x = ");
df.writeLine(x.toString());
// covariance matrix
MinCov mc = new MinCov(x, mllg);
cx = mc.getCovarianceMatrix(1.);
df.writeLine("Covariance Matrix cx = ");
df.writeLine(cx.toString());
// asymmetric errors
fcont = fcont + 0.5;
MinAsy ma = new MinAsy(x, cx, mllg);
dxasy = ma.getAsymmetricErrors(fcont);
DatanMatrix as = new DatanMatrix(dxasy);
df.writeLine("Asymmetic errors:");
df.writeLine(as.toString());
df.writeLine("ma.hasConverged() = " + ma.hasConverged());
plotScatterDiagram();
plotParameterPlane();
}
