R/sampling_hrm_phi.R

In immer: Item Response Models for Multiple Ratings

## File Name: sampling_hrm_phi.R
## File Version: 0.252

###########################################################
# sampling phi parameters
sampling_hrm_phi <- function( dat, dat_ind, maxK, R, rater, pid, phi, psi,
        prior, MHprop, I, xi, useRcpp, est_settings  )
{
    eps <- 1E-20
    MHprop$refresh_count$phi <- MHprop$refresh_count$phi + 1
    est.phi <- est_settings$est.phi
    if ( est.phi=='r')
    {
        ratio1 <- log( rep(1,R) )
    }
    if ( est.phi !='n' )
    {
        for (ii in 1L:I)
        {
            if ( est.phi=='a')
            {
                phi_new <- phi_old <- phi
                phi_new[ii,] <- stats::rnorm( R, mean=phi[ii,],
                                            sd=MHprop$SD$phi[ii,] )
            }
            if ( ( est.phi=='r' ) & ( ii==1 ) )
            {
                phi_new <- phi_old <- phi
                phi_new[1L:I,] <- matrix( stats::rnorm( R, mean=phi[1,],
                                            sd=MHprop$SD$phi[1,] ),
                                            nrow=I, ncol=R, byrow=TRUE )
            }
            if ( ( est.phi=='a' ) | ( ii==1 ) )
            {
                p_new <- stats::dnorm( phi_new[ii,], mean=prior$phi$M[ii,],
                                        sd=prior$phi$SD[ii,] )
                p_old <- stats::dnorm( phi_old[ii,], mean=prior$phi$M[ii,],
                                        sd=prior$phi$SD[ii,] )
            } else
            {
                p_new <- p_old <- rep(1,R)
            }
            ll_new <- probs_hrm( x=dat[,ii], xi=xi[ pid, ii ],
                                    phi=phi_new[ ii, rater ],
                                    psi=psi[ii,rater ], K=maxK[ii],
                                    x_ind=dat_ind[,ii], useRcpp=useRcpp )
            ll_new <- rowsum( log( ll_new + eps ), rater )[,1]
            ll_old <- probs_hrm( x=dat[,ii], xi=xi[ pid, ii ],
                                    phi=phi_old[ ii, rater ],
                                    psi=psi[ii,rater ], K=maxK[ii],
                                    x_ind=dat_ind[,ii], useRcpp=useRcpp  )
            ll_old <- rowsum( log( ll_old + eps ), rater )[,1]

            ratio <- immer_sampling_calc_ratio( ll_old=ll_old, ll_new=ll_new,
                            p_old=p_old, p_new=p_new, eps=eps )

            if ( est.phi=='r')
            {
                ratio1 <- log( ratio ) + ratio1
            }

            # estimate phi[i,r]
            if ( est.phi=='a' ){
                for (rr in 1L:R){
                    if( is.na(ratio[rr] ) ){ ratio[rr] <- 0 }
                        if ( ratio[rr] > stats::runif(1) ){
                            MHprop$accept$phi[ii,rr] <- MHprop$accept$phi[ii,rr] + 1
                                    phi[ii,rr] <- phi_new[ii,rr]
                    }
                }  # end rr
            }  # end est.phi=='a'
        }  # end ii
        ####****
        if ( est.phi=='r' ){
            for (rr in 1L:R){
                ratio[rr] <- exp(ratio1[rr])
                if( is.na(ratio[rr] ) ){
                    ratio[rr] <- 0
                }
                if ( ratio[rr] > stats::runif(1) ){
                    MHprop$accept$phi[1L:I,rr] <- MHprop$accept$phi[1L:I,rr] + 1
                    phi[1L:I,rr] <- phi_new[1L:I,rr]
                }
            }  # end rr
        }  # end est.phi=='r'
    }
    res <- list( phi=phi, MHprop=MHprop )
    return(res)
}