better variance computation, use Knuth online robust algorithm, add a test for variance computation

edo/test/t-variance.cpp

@@ -0,0 +1,38 @@
+
+#include <iostream>
+#include <vector>
+
+#include <eo>
+#include <es.h>
+#include <edo>
+
+int main()
+{
+    typedef eoReal<eoMinimizingFitness> Vec;
+
+    eoPop<Vec> pop;
+    for( unsigned int i=1; i<7; ++i) {
+        Vec indiv(1,i);
+        pop.push_back( indiv );
+        std::clog << indiv << " ";
+    }
+    std::clog << std::endl;
+
+    edoEstimatorNormalMono<Vec> estimator;
+
+    edoNormalMono<Vec> distrib = estimator(pop);
+
+    Vec ex_mean(1,3.5);
+    Vec ex_var(1,17.5/6);
+    Vec es_mean = distrib.mean();
+    Vec es_var = distrib.variance();
+
+    std::cout << "expected  mean=" << ex_mean << " variance=" << ex_var << std::endl;
+    std::cout << "estimated mean=" << es_mean << " variance=" << es_var << std::endl;
+
+    for( unsigned int i=0; i<ex_mean.size(); ++i ) {
+        assert( es_mean[i] == ex_mean[i] );
+        assert(  es_var[i] == ex_var[i] );
+    }
+}
+