lot of fixes, XYSampleData fit now seems to work (more checks are probably needed)

examples/exFitSample.cpp

@@ -0,0 +1,54 @@
+#include <iostream>
+#include <cmath>
+#include <LatAnalyze/CompiledModel.hpp>
+#include <LatAnalyze/MinuitMinimizer.hpp>
+#include <LatAnalyze/RandGen.hpp>
+#include <LatAnalyze/XYSampleData.hpp>
+
+using namespace std;
+using namespace Latan;
+
+const Index  nPoint  = 30;
+const Index  nSample = 1000;
+const double xErr = .2, yErr   = .1;
+const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast<double>(nPoint);
+
+int main(void)
+{
+    // generate fake data
+    DMatSample   x(nSample, nPoint, 1), y(nSample, nPoint, 1);
+    XYSampleData data(nSample);
+    RandGen     rg;
+    double      x1_k, x2_k;
+    DoubleModel f([](const double *t, const double *p)
+                  {return p[1]*exp(-t[0]*p[0]);}, 1, 2);
+    
+    data.addXDim("x", nPoint);
+    data.addYDim("y");
+    FOR_STAT_ARRAY(x, s)
+    {
+        for (Index k = 0; k < nPoint; ++k)
+        {
+            x1_k         = rg.gaussian(k*dx, xErr);
+            x2_k         = rg.gaussian(k*dx, xErr);
+            data.x(k)[s] = x1_k;
+            data.y(k)[s] = rg.gaussian(f(&x2_k, exactPar), yErr);
+        }
+    }
+    cout << data << endl;
+    
+    // fit
+    DVec init = DVec::Constant(2, 0.5);
+    DMat err;
+    SampleFitResult p;
+    MinuitMinimizer minimizer;
+    
+    p   = data.fit(minimizer, init, f);
+    err = p.variance().cwiseSqrt();
+    cout << "a= " << p[central](0) << " +/- " << err(0) << endl;
+    cout << "b= " << p[central](1) << " +/- " << err(1) << endl;
+    cout << "chi^2/ndof= " << p.getChi2PerDof() << endl;
+    cout << "p-value= " << p.getPValue() << endl;
+    
+    return EXIT_SUCCESS;
+}