我正在尝试集成函数，包括使用ICDF函数（gsl_cdf_gaussian_Pinv(x[1], 1)）更改变量，但结果总是错误的：
#include <fstream>
#include <iostream>
#include <memory>
#include <cmath>
#include <iomanip>
#include <ctime>
#include <cmath>
#include <cstdlib>
#include <ctime>
#include <math.h>
#include <stdio.h>
#include <gaussinv.c>
#define _USE_MATH_DEFINES
using namespace std;
double f(double[], int);
double int_mcnd(double(*)(double[], int), double[], double[], int, int);
double varr[100];
int k = 0;
double hj = 0;
double mj = 1;
# include "sobol.hpp"
int DIM_NUM = 10;
int main() {
const int n = 10; /* define how many integrals */
// const int m = 1000000; /* define how many points */
double a[n] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; /* left end-points */
double b[n] = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; /* right end-points */
double result;
int i, m;
int ntimes;
cout.setf(ios::fixed | ios::showpoint);
// current time in seconds (begin calculations)
time_t seconds_i;
seconds_i = time(NULL);
m = 1; // initial number of intervals
ntimes = 20; // number of interval doublings with nmax=2^ntimes
cout << setw(12) << n << "D Integral" << endl;
for (i = 0; i <= ntimes; i = i + 1) {
result = int_mcnd(f, a, b, n, m);
cout << setw(10) << m << " " << setprecision(30) << result << endl;
m = m * 2;
}
// current time in seconds (end of calculations)
time_t seconds_f;
seconds_f = time(NULL);
cout << endl << "total elapsed time = " << seconds_f - seconds_i << " seconds" << endl << endl;
return 0;
}
double f(double x[], int n) {
double y;
int j;
y = 0.0;
/* define Multidimensional Gaussian distribution and covariance */
/* X=(x1, k=2, mu = (0, covariance matrix = (v 0 0 0
* x2 0 0 v 0 0
* x3 0 0 0 v 0
* x4) 0) 0 0 0 v) */
double v = 1;
double determinant = pow(v, 10);
double inverse = 1 / v;
double rang = gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1) - gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1) +
gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1);
y = (1 / sqrt(pow(2 * M_PI, 10) * determinant) * exp(-0.5 * (inverse * pow(gsl_cdf_gaussian_Pinv(x[0], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[1], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[2], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[3], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[4], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[5], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[6], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[7], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[8], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[9], 1), 2))));
return y;
}
/*==============================================================
input:
fn - a multiple argument real function (supplied by the user)
a[] - left end-points of the interval of integration
b[] - right end-points of the interval of integration
n - dimension of integral
m - number of random points
output:
r - result of integration
================================================================*/
double int_mcnd(double(*fn)(double[], int), double a[], double b[], int n, int m) {
double r, x[n], p;
int i, j;
double rarr[DIM_NUM];
long long int seed;
seed = 1;
long long int seed_in;
long long int seed_out;
srand(time(NULL)); /* initial seed value (use system time) */
r = 0.0;
p = 1.0;
// step 1: calculate the common factor p
for (j = 0; j < n; j = j + 1) {
// p = p * (b[j] - a[j]);
p=p*(gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1)-gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1));
}
// step 2: integration
for (i = 1; i <= m; i = i + 1) {
seed_in = seed;
i8_sobol(DIM_NUM, &seed, rarr);
seed_out = seed;
// calculate random x[] points
for (j = 0; j < n; j = j + 1) {
x[j] = a[j] + (b[j] - a[j]) * rarr[j];
}
r = r + fn(x, n);
}
cout << endl << "p = " << p << " seconds" << endl << endl;
r = r * p / m;
return r;
}
问题出在参数化参数p中，我建议
p=p*(gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1)-gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1))
而不是标准 - p = p * (b[j] - a[j]);
我想不仅要在[0,1] ^ N区间内进行整合，还要在[-20; 20]进行整合。
我无法定义我的错误。有人可以帮帮忙吗？