NormalDistribution::NormalDistribution(const Mean& m,
const StdDeviation& sigma)
: DistributionBase(), mean_(m.value()), stdDev_(sigma.value())
{
if(stdDev_ < 0.0)
throw runtime_error("NormalDistribution : in ctor, sigma must be positive.");
lower_ = mean_ - stdDev_*2;
upper_ = mean_ + stdDev_*2;
pLower_ = getUntruncatedCDF(lower_);
pUpper_ = getUntruncatedCDF(upper_);
}
NormalDistribution::NormalDistribution(const Mean& m,
const StdDeviation& sigma,
double numDeviations)
: DistributionBase(), mean_(m.value()), stdDev_(sigma.value())
{
if(stdDev_ < 0.0)
throw std::runtime_error("NormalDistribution : in ctor, sigma must be positive.");
if(numDeviations < 0.0)
throw runtime_error("NormalDistribution : in ctor, numDevations must be positive.");
lower_ = mean_ - numDeviations*stdDev_;
upper_ = mean_ + numDeviations*stdDev_;
pLower_ = getUntruncatedCDF(lower_);
pUpper_ = getUntruncatedCDF(upper_);
}
int main(void)
{
int array[] = { 10, 2, 3, 34, 3, 4, 45, 99 };
int array_size = sizeof( array ) / sizeof( array[0] );
Mean< int > mean;
for ( unsigned int i = 0; i < array_size; ++i )
{
mean( array[i] );
}
std::cout << "mean: " << mean.value() << std::endl;
return 0;
}