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-rw-r--r--src/stratified_sampling.hpp29
1 files changed, 14 insertions, 15 deletions
diff --git a/src/stratified_sampling.hpp b/src/stratified_sampling.hpp
index 9099e38..9175f75 100644
--- a/src/stratified_sampling.hpp
+++ b/src/stratified_sampling.hpp
@@ -3,7 +3,6 @@
#include <iostream>
#include "var_alea.hpp"
#include <gsl/gsl_cdf.h>
-#include "option.hpp"
using namespace std;
@@ -14,14 +13,14 @@ struct gaussian_truncated : var_alea<double>
{
gaussian_truncated(double a, double b, double mu = 0, double sigma = 1)
:a(a), b(b), V(gsl_cdf_ugaussian_P(a), gsl_cdf_ugaussian_P(b)), mu(mu), sigma(sigma) {};
-
+
double operator()() {
double v = V();
return mu + gsl_cdf_gaussian_Pinv(v,sigma);
}
-
+
private:
- double a, b;
+ double a, b;
uniform V;
double mu;
double sigma;
@@ -31,7 +30,7 @@ struct multi_gaussian_truncated : public var_alea<std::vector<double> >
{
multi_gaussian_truncated(double a, double b, const std::vector<double> u)
:a(a), b(b), V(gsl_cdf_ugaussian_P(a), gsl_cdf_ugaussian_P(b)), G(0,1), u(u), d(u.size()) {};
-
+
std::vector<double> operator()() {
double v = V();
double Z = gsl_cdf_gaussian_Pinv(v,1);
@@ -49,9 +48,9 @@ struct multi_gaussian_truncated : public var_alea<std::vector<double> >
}
return X;
}
-
+
private:
- double a, b;
+ double a, b;
uniform V;
gaussian G;
std::vector<double> u;
@@ -180,15 +179,16 @@ pair<double,double> stratified_sampling<L>::estimator() const {
return {est_mean, est_std};
}
-struct f_mu : public std::unary_function<std::vector<double>, double>
+template <typename Fct>
+struct exponential_tilt : public std::unary_function<std::vector<double>, double>
{
- f_mu(std::vector<double> mu, asian_option A) : mu(mu), A(A){
+ exponential_tilt(std::vector<double> mu, Fct f) : mu(mu), f(f){
norm_mu = 0;
for(unsigned int i=0; i<mu.size(); i++) {
norm_mu += mu[i]*mu[i];
}
};
-
+
double operator()(std::vector<double> X) {
std::vector<double> Y(X.size());
double scal = 0;
@@ -196,12 +196,11 @@ struct f_mu : public std::unary_function<std::vector<double>, double>
Y[i] = X[i] + mu[i];
scal+=X[i]*mu[i];
}
- return A(Y)*exp(-scal-0.5*norm_mu);
+ return f(Y) * exp(-scal-0.5*norm_mu);
};
-
- private :
+
+ private:
std::vector<double> mu;
- asian_option A;
+ Fct f;
double norm_mu;
};
-