Generates pseudorandom numbers from a Student’s t distribution.
#include <imsls.h>
float *imsls_f_random_student_t (int n_random, float df, ..., 0)
The type double function is imsls_d_random_student_t.
int n_random
(Input)
Number of random numbers to generate.
float df
(Input)
Degrees of freedom. Parameter df must be
positive.
An array of length n_random containing the random deviates of a Student’s t distribution.
#include <imsls.h>
float
*imsls_f_random_student_t (int n_random,
float
df,
IMSLS_MEAN,
float
mean,
IMSLS_VARIANCE,
float
variance,
IMSLS_RETURN_USER,
float r[],
0)
IMSLS_MEAN, float mean
(Input)
Mean of the Student’s t
distribution.
Default: mean =
0.0
IMSLS_VARIANCE, float variance
(Input)
Variance of the Student’s t
distribution.
Default: variance =
1.0
IMSLS_RETURN_USER, float r[]
(Output)
User-supplied array of length n_random containing
the random Student’s t deviates.
Function imsls_f_random_student_t generates pseudorandom numbers from a Student’s t distribution with df degrees of freedom, using a method suggested by Kinderman et al. (1977). The method (“TMX” in the reference) involves a representation of the t density as the sum of a triangular density over (−2, 2) and the difference of this and the t density. The mixing probabilities depend on the degrees of freedom of the t distribution. If the triangular density is chosen, the variate is generated as the sum of two uniforms; otherwise, an acceptance/rejection method is used to generate the difference density.
In this example, imsls_f_random_student_t generates five pseudorandom deviates from a Student’s t distribution with 12 degrees of freedom.
#include <imsls.h>
#include <stdio.h>
int main()
{
int seed = 123457, n_random = 5;
float df = 12.0, *r;
imsls_random_seed_set (seed);
r = imsls_f_random_student_t (n_random, df, 0);
printf("Student's t deviates with %8.4f degrees "
"of freedom:", df);
printf("\n%8.4f %8.4f %8.4f %8.4f %8.4f\n",
r[0], r[1], r[2], r[3], r[4]);
}
Output
Student's t deviates with 12.0000 degrees of freedom:
0.6152 1.1468 0.0877 1.3318 -0.9933