void LS::draw(){
impute_latent_data();
draw_beta();
}
void BLSSS::draw() {
impute_latent_data();
if(allow_model_selection_) draw_model_indicators();
draw_beta();
}
extern "C" void glm_gibbs(double * rZ, double * rxo, double * rlam, int * rmodelprior, double * rpriorprob, double * rbeta1, double * rbeta2, int * rburnin, int * rniter, int * rscalemixture, double * ralpha, int * rno, int * rna, int * rp, double * B_mcmc, double * prob_mcmc, int * gamma_mcmc, double * phi_mcmc, double * lam_mcmc, double * B_rb, double * prob_rb, double * intercept_mcmc, double * xo_scale)
{
GetRNGstate();
//MCMC Variables//
int burnin=*rburnin;
int niter=*rniter;
//Dimensions//
int p=*rp;
int no=*rno;
int na=*rna;
//Phi Variables//
double phi=1.0;
//Yo Variables//
std::vector<double> Z(rZ, rZ+no);
std::vector<double> xo(rxo, rxo+no*p);
standardize_xo(xo,xo_scale,no,p);
std::vector<double> xoyo(p);
double yobar=0;
std::vector<double> xoxo(p*p);
dgemm_( &transT, &transN, &p, &p, &no, &unity, &*xo.begin(), &no, &*xo.begin(), &no, &inputscale0, &*xoxo.begin(), &p );
//Construct Xa//
std::vector<double> xa(p*(p+1)/2); //Triangular Packed Storage
std::vector<double> d(p);
chol_xa(xa,xoxo,d,p);
//Reserve Memory for Submatrices//
std::vector<double> xog; xog.reserve(no*p);
std::vector<double> xogyo; xogyo.reserve(p);
std::vector<double> xogxog_Lamg; xogxog_Lamg.reserve(p*p);
std::vector<double> xag; xag.reserve(na*p);
//Ya Variables//
std::vector<double> xaya(p);
//Beta Variables//
double intercept=0;
std::vector<double> Bols(p);
std::vector<double> B(p,0.0);
std::vector<double> Bg; Bg.reserve(p);
//Lambda Variables//
int scalemixture=*rscalemixture;
double alpha=*ralpha;
std::vector<double> lam(rlam,rlam+p);
std::vector<double> lamg; lamg.reserve(p); //vector instead of diagonal pxp matrix
//Gamma Variables//
std::vector<int> gamma(p,1);
int p_gamma=std::accumulate(gamma.begin(),gamma.end(),0);
bool gamma_diff=true;
int modelprior=*rmodelprior;
//Probability Variables//
std::vector<double> prob(p);
std::vector<double> odds(p);
std::vector<double> priorprob(rpriorprob,rpriorprob+p);
//Theta Variables//
double theta=0.5;
double beta1=*rbeta1;
double beta2=*rbeta2;
//Store Initial Values//
std::copy(B.begin(),B.end(),B_mcmc);
std::copy(prob.begin(),prob.end(),prob_mcmc);
std::copy(gamma.begin(),gamma.end(),gamma_mcmc);
std::copy(lam.begin(),lam.end(),lam_mcmc);
//Run Gibbs Sampler//
for (int t = 1; t < niter; ++t)
{
//Form Submatrices//
if(p_gamma) submatrices_uncollapsed(gamma_diff,B,xog,xag,lamg,Bg,gamma,lam,xo,xa,p_gamma,p,no,na);
//Draw xoyo//
draw_xoyo(Z,xoyo,yobar,xo,xog,Bg,phi,no,p,p_gamma,intercept);
//Draw xaya//
draw_uncollapsed_xaya(xaya,xa,xag,Bg,phi,na,p,p_gamma);
//Compute Probabilities//
if(modelprior==1)
{
bernoulli_probabilities(prob,odds,Bols,d,xoyo,xaya,priorprob,lam,phi);
}else if(modelprior==2)
{
betabinomial_probabilities(prob,odds,Bols,d,xoyo,xaya,theta,lam,phi);
}else
{
uniform_probabilities(prob,odds,Bols,d,xoyo,xaya,lam,phi);
}
//Draw Gamma//
draw_gamma(gamma,p_gamma,prob);
//Draw Theta//
if(modelprior==2) theta=Rf_rbeta(beta1+p_gamma,p-p_gamma+beta2);
//Draw Beta//
draw_beta(gamma,B,Bols,d,lam,phi);
//Draw Intercept//
intercept=yobar+sqrt(1/(no*phi))*Rf_rnorm(0,1);
//Draw Lambda//
if(scalemixture) draw_lambda_t(lam,gamma,alpha,B,phi);
//Store Draws//
intercept_mcmc[t]=intercept;
std::copy(gamma.begin(),gamma.end(),(gamma_mcmc+p*t));
std::copy(prob.begin(),prob.end(),(prob_mcmc+p*t));
std::copy(B.begin(),B.end(),(B_mcmc+p*t));
std::copy(lam.begin(),lam.end(),(lam_mcmc+p*t));
//Rao Blackwell//
if(t>=burnin) rao_blackwell(B_rb,prob_rb,B,prob,burnin,niter);
//Has Gamma Changed?//
gamma_diff=gamma_change(gamma_mcmc,t,p);
}
PutRNGstate();
}
