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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
|---|---|---|
| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/KPMstats/student_t_logprob.m | |
| parent | 7cc31810d53176e805532b2789955f4eedbce6bb (diff) | |
| download | BNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz | |
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02
Diffstat (limited to 'sourcecodes/bnt-master/KPMstats/student_t_logprob.m')
| -rw-r--r-- | sourcecodes/bnt-master/KPMstats/student_t_logprob.m | 13 |
1 files changed, 13 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/KPMstats/student_t_logprob.m b/sourcecodes/bnt-master/KPMstats/student_t_logprob.m new file mode 100644 index 00000000..0aea837e --- /dev/null +++ b/sourcecodes/bnt-master/KPMstats/student_t_logprob.m @@ -0,0 +1,13 @@ +function L = log_student_pdf(X, mu, lambda, alpha) +% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point +% L = log_student_pdf(X, mu, lambda, alpha) +% +% Each column of X is evaluated. +% See Bernardo and Smith p435. + +k = length(mu); +assert(size(X,1) == k); +[k N] = size(X); +logc = gammaln(0.5*(alpha+k)) - gammaln(0.5*alpha) - (k/2)*log(alpha*pi) + 0.5*log(det(lambda)); +middle = (1 + (1/alpha)*(X-mu)'*lambda*(X-mu)); % scalar version +L = logc - ((alpha+k)/2)*log(middle); |
