Fix undefined default initialization

It worked because VecCore depends on the backend default
initialization (in this case Vc initializes to 0.)

math/mathcore/inc/Fit/EvaluateChi2.hxx

@@ -133,7 +133,7 @@ struct Chi2 {
             x = &x1;
          }
 
-         T fval{};
+         T fval(0.);
 
 #ifdef USE_PARAMCACHE
          fval = func(x);
@@ -152,7 +152,7 @@ struct Chi2 {
          return chi2;
       };
 
-      auto redFunction = [](const std::vector<T> &objs) { return std::accumulate(objs.begin(), objs.end(), T{}); };
+      auto redFunction = [](const std::vector<T> &objs) { return std::accumulate(objs.begin(), objs.end(), T(0.)); };
 
 #ifndef R__USE_IMT
       (void)nChunks;
@@ -165,7 +165,7 @@ struct Chi2 {
       }
 #endif
 
-      T res{};
+      T res(0.);
       if (executionPolicy == ROOT::Fit::ExecutionPolicy::kSerial) {
          ROOT::TSequentialExecutor pool;
          res = pool.MapReduce(mapFunction, ROOT::TSeq<unsigned>(0, data.Size() / vecSize), redFunction);

math/mathcore/inc/Fit/EvaluateLogL.hxx

@@ -48,7 +48,7 @@ namespace FitUtil {
 template <class T>
 class LikelihoodAux {
 public:
-   LikelihoodAux(T logv = {}, T w = {}, T w2 = {}) : logvalue(logv), weight(w), weight2(w2) {}
+   LikelihoodAux(T logv = 0., T w = 0., T w2 = 0.) : logvalue(logv), weight(w), weight2(w2) {}
 
    LikelihoodAux operator+(const LikelihoodAux &l) const
    {
@@ -180,9 +180,9 @@ struct LogL {
       unsigned int numVectors = n / vecSize;
 
       auto mapFunction = [&, p](const unsigned i) {
-         T W{};
-         T W2{};
-         T fval{};
+         T W(0.);
+         T W2(0.);
+         T fval(0.);
 
          (void)p; /* avoid unused lambda capture warning if PARAMCACHE is disabled */
 
@@ -222,7 +222,7 @@ struct LogL {
          // function EvalLog protects against negative or too small values of fval
          auto logval = ROOT::Math::Util::EvalLog(fval);
          if (iWeight > 0) {
-            T weight{};
+            T weight(0.);
             if (data.WeightsPtr(i) == nullptr)
                weight = 1;
             else
@@ -262,9 +262,9 @@ struct LogL {
       }
 #endif
 
-      T logl_v{};
-      T sumW_v{};
-      T sumW2_v{};
+      T logl_v(0.);
+      T sumW_v(0.);
+      T sumW2_v(0.);
       ROOT::Fit::FitUtil::LikelihoodAux<T> resArray;
       if (executionPolicy == ROOT::Fit::ExecutionPolicy::kSerial) {
          ROOT::TSequentialExecutor pool;

math/mathcore/inc/Fit/EvaluatePoissonLogL.hxx

@@ -105,7 +105,7 @@ struct PoissonLogL {
       auto mapFunction = [&](unsigned int i) {
          T y;
          vecCore::Load<T>(y, data.ValuePtr(i * vecSize));
-         T fval{};
+         T fval(0.);
 
          if (data.NDim() > 1) {
             std::vector<T> x(data.NDim());
@@ -131,7 +131,7 @@ struct PoissonLogL {
          // negative values of fval
          vecCore::MaskedAssign<T>(fval, fval < 0.0, 0.0);
 
-         T nloglike{}; // negative loglikelihood
+         T nloglike(0.); // negative loglikelihood
 
          if (useW2) {
             // apply weight correction . Effective weight is error^2/ y
@@ -168,7 +168,7 @@ struct PoissonLogL {
       };
 
 #ifdef R__USE_IMT
-      auto redFunction = [](const std::vector<T> &objs) { return std::accumulate(objs.begin(), objs.end(), T{}); };
+      auto redFunction = [](const std::vector<T> &objs) { return std::accumulate(objs.begin(), objs.end(), T(0.)); };
 #else
       (void)nChunks;