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function L = log_marg_prob_node(CPD, self_ev, pev)
% LOG_MARG_PROB_NODE Compute prod_m log P(x(i,m)| x(pi_i,m)) for node i (root_gaussian)
% L = log_marg_prob_node(CPD, self_ev, pev)
%
% This differs from log_prob_node because we integrate out the parameters.
% self_ev{m} is the evidence on this node in case m.
% pev{i,m} is the evidence on the i'th parent in case m (ignored).
ncases = length(self_ev);
if ncases==0
L = 0;
return;
elseif ncases==1
x = cat(1, self_ev{:});
k = length(x);
n0 = CPD.prior.n;
mu = CPD.prior.mu;
alpha = CPD.prior.alpha;
beta = CPD.prior.beta;
gamma = 2*alpha - k + 1;
% Bernardo and Smith p441
L = log_student_pdf(x, mu, n0/(n0+1)*0.5*gamma*inv(beta), gamma);
else
error('can''t handle batch data');
end
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