Judging from the documentation boost seems to offer quantile functions (inverse cdf functions) for both normal and gamma distributions, but its not clear for me how can I actually use them. Could someone paste an example please?
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问题:
回答1:
The quantile calculation is implemented as a free function. Here's an example:
#include <boost/math/distributions/normal.hpp>
boost::math::normal dist(0.0, 1.0);
// 95% of distribution is below q:
double q = quantile(dist, 0.95);
You can also get the complement (quantile from the right) using:
// 95% of distribution is above qc:
double qc = quantile(complement(dist, 0.05));
There are some similar worked examples here:
http://www.boost.org/doc/libs/1_46_1/libs/math/doc/sf_and_dist/html/math_toolkit/dist/stat_tut/weg.html
Edit: don't need namespaces on the free functions thanks to ADL
回答2:
There is a workable example on QuantCorner.
// Édouard Tallent @ TaGoMa.Tech
// September 2012
#include<boost/math/distributions.hpp>
#include<iostream>
using std::cout;
using std::endl;
double inverseNormal(double prob, double mean, double sd){
boost::math::normal_distribution<>myNormal (mean, sd);
return quantile(myNormal, prob);
}
int main (int, char*[])
{
try
{
double myProb = 0.1; // the 10% quantile
double myMean = 0.07; // a 7% mean
double myVol = 0.14; // a 14% volatility
cout << inverseNormal(myProb, myMean, myVol) << endl;
}
catch(std::exception& e)
{
cout << "Error message: " << e.what() << endl;
}
return 0;
}