You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: bic_score_family.m
    path of file: ./repos/bnt/BNT/learning
    
    the code of the file until where you have to start completion: function [S, LL] = bic_score(counts, CPT, ncases)
% BIC_SCORE Bayesian Information Criterion score for a single family
% [S, LL] = bic_score(counts, CPT, ncases)
%
% S is a large sample approximation to the log marginal likelihood,
% which can be computed using dirichlet_score.
%
% S  = \log [ prod_j _prod_k theta_ijk ^ N_ijk ]  - 0.5*d*log(ncases) 
% where counts encode N_ijk, theta_ijk is the MLE comptued from counts,
% and d is the num of free parameters.

%CPT = mk_stochastic(counts);
tiny = exp(-700);

    
function [S, LL] = bic_score(counts, CPT, ncases)
% BIC_SCORE Bayesian Information Criterion score for a single family
% [S, LL] = bic_score(counts, CPT, ncases)
%
% S is a large sample approximation to the log marginal likelihood,
% which can be computed using dirichlet_score.
%
% S  = \log [ prod_j _prod_k theta_ijk ^ N_ijk ]  - 0.5*d*log(ncases) 
% where counts encode N_ijk, theta_ijk is the MLE comptued from counts,
% and d is the num of free parameters.

%CPT = mk_stochastic(counts);
tiny = exp(-700);
LL = sum(log(CPT(:)  + tiny) .* counts(:));
% CPT(i) = 0 iff counts(i) = 0 so it is okay to add tiny

ns = mysize(counts);
ns_ps = ns(1:end