While the random module allows one to generate randome numbers with a
variety of distributions, some useful distributions are omitted - the
Student's t being among them. This distribution is easily derived from
the normal distribution and the chi-squared distribution (which in
turn is a special case of the gamma distribution). I edited and tested
a routine to generate random variables with a Student's t distribution
that I found on http://www.johndcook.com/python_student_t_rng.html,
which has one bug - there is an extra factor of two in y. The
corrected and tested code follows - how does one go about getting this
incorporated into random so that the entire community can beneffit
from it?
Sincerely
Thomas Philips
def student_t(df): # df is the number of degrees of freedom
if df < 2 or int(df) != df:
raise ValueError, 'student_tvariate: df must be a integer > 1'
x = random.gauss(0, 1)
y = random.gammavariate(df/2.0, 2)
return x / (math.sqrt(y/df))
References:
1. Student's t distribution, including relationship to normal and chi-
squared distributions: http://en.wikipedia.org/wiki/Student's_t-distribution
2. Chi-squared distribution, including relationship to Gamma
distribution: http://en.wikipedia.org/wiki/Chi-square_distribution
3. John Cook's original version (with the extra factor of 2):
http://www.johndcook.com/python_student_t_rng.html
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