C语言 为什么不计算伽马变量的均方误差?

Question

因此，我编写了这段代码，用于计算不同样本和贝塔值的alpha和beta的均方估计。alpha的值是3，因为我们添加了三个指数分布来创建gamma变量。

然而，这段代码没有给我任何正确的输出。

# include <stdio.h>
# include <math.h>
# include <stdlib.h> // Don't forget to include this
main()
{
int n,N; // Sample size and number of simulations
long double alpha=3,beta,suma=0.0,sumb=0.0,msea,mseb;  
int i,j,k;
printf("Enter the number of simulations");
scanf("%d", &N);
printf("Enter the sample size");
scanf("%d", &n);
printf("Enter the value of beta");
scanf("%Lf", &beta);
//Simulation starts to calculate MSE
for(i=0;i<N;i++)
{
float msea=0.0,mseb=0.0,sum=0.0,sumsq=0.0; //Vlaue is reset at every iteration, so declared inside i loop
for(j=0;j<n;j++)//each sample
{
float g;
for(k=0;k<alpha;k++)
g += (double)(-1/beta)*log(1-((double)rand()/RAND_MAX));//sum of exp is gamma
sum += g;
sumsq += g*g;
}
float xbar = sum/n;
float var = sumsq/n - xbar*xbar;
suma += pow ((xbar*xbar/var - alpha),2);
sumb += pow ((xbar/var - beta),2);
}
msea = suma/n;
mseb = sumb/n;
printf("MSE of alpha is = %Lf", msea);
printf("MSE of beta is = %Lf", mseb);

return 0;
}

你能帮我找出我的错误吗?

Answer 1

代码至少存在这些问题:

未初始化的g

float g;
for (k = 0; k < alpha; k++)
g += (double) (-1 / beta) * log(1 - ((double) rand() / RAND_MAX)); 

log(0)

log(1-((double)rand()/RAND_MAX))可能传递log(0)。我怀疑log(1 - (((double) rand() + 0.5)/ (RAND_MAX + 1u)))将提供更好的分发。

3 FP类型

在float, double, long double中有很多向上转换，向下转换。

一直使用double，直到确定需要其他宽度为止。

<<p>

未使用的对象/strong>float msea=0.0,mseb=0.0不使用。提示:启用所有警告，节省时间。

<<p>

使用% g/strong>"%g"信息更丰富。

// printf("MSE of alpha is = %Lf", msea);
printf("MSE of alpha is = %Lg", msea);

---

OP报告"我做了更改，它仍然没有输出"。我得到了

MSE of alpha is = 105.474
MSE of beta is = 31.4536

我怀疑OP没有做所有的更改。

# include <stdio.h>
# include <math.h>
# include <stdlib.h> // Don't forget to include this
int main() {
int n, NN; // Sample size and number of simulations
double alpha = 3, beta, suma = 0.0, sumb = 0.0, msea, mseb;
int i, j, k;
printf("Enter the number of simulations");
//  scanf("%d", &NN);
printf("Enter the sample size");
//  scanf("%d", &n);
printf("Enter the value of beta");
//  scanf("%f", &beta);
NN = 1000;
n = 20;
beta = 1.5;
//Simulation starts to calculate MSE
for (i = 0; i < NN; i++) {
double sum = 0.0, sumsq = 0.0; //Vlaue is reset at every iteration, so declared inside i loop
for (j = 0; j < n; j++) //each sample
{
double g = 0;
for (k = 0; k < alpha; k++)
g += (double) (-1 / beta)
* log(1 - (((double) rand() + 0.5) / (RAND_MAX + 1u)));
sum += g;
sumsq += g * g;
}
double xbar = sum / n;
double var = sumsq / n - xbar * xbar;
suma += pow((xbar * xbar / var - alpha), 2);
sumb += pow((xbar / var - beta), 2);
}
msea = suma / n;
mseb = sumb / n;
printf("MSE of alpha is = %gn", msea);
printf("MSE of beta is = %gn", mseb);
return 0;
}