Thanks Paul. Actually I didn't read the testing sources. However, are the links to the math.pdf broken? (Perhaps it's just me, who cannot download this pdf right now. Or I just have a bad day ...) The solution: I did indeed make a most stupid mistake: When you miscalculate N, the distribution you compare against is wrong and in the extreme, you get only zeros back (which happend to me). Arrgh! *headbang* ;-) Thanks, Christian On Fri, 2010-04-09 at 12:14 +0100, Paul A. Bristow wrote:
-----Original Message----- From: boost-users-bounces@lists.boost.org [mailto:boost-users-bounces@lists.boost.org] On Behalf Of Christian Meesters Sent: Friday, April 09, 2010 11:21 AM To: boost-users@lists.boost.org Subject: [Boost-users] [math/distributions] calculating p-value?
Hi,
Having a test which values are chi^2-distributed, I tried to calculate a p-value and utterly failed.
My code, so far:
#include
using boost::math::chi_squared; <snip> chi_squared dist(N - 1); p = cdf(complement(dist, (std::fabs(beta)))) ; Here, N is the sample size and beta my beta-estimate.
Reading Numerical Recipies my approach might be a bit naive, yet is there any short hand using boost? (Or am I making a stupid mistake here?
Nothing obvious jumps out at me.
It appears you have seem the example at
boost_1_42_0\libs\math\example\chi_square_std_dev_test.cpp
and test_chi_squared.cpp has this very similar code
BOOST_CHECK_CLOSE( cdf(complement(dist, cs)), Q, tol);
and you have also seen the section in math.pdf on non-member properties, like cdf and when to use complements and why.
Have you used a try'n'catch block around your call?
without this, if things go wrong it will end silently (no error messages!), and unhappily for you ;-)
See page 63 of math.pdf for some discussion and examples.
HTH
Paul
--- Paul A. Bristow Prizet Farmhouse Kendal, UK LA8 8AB +44 1539 561830, mobile +44 7714330204 pbristow@hetp.u-net.com
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