R/mu_d_beta_faster.R

In statdivlab/tinyvamp: Modeling complex measurement error in microbiome experiments

mu_d_beta_faster <- function(i,
                             J,
                             k,
                             gammas,
                             B,
                             X,
                             Z,
                             P,
                             X_tilde,
                             Z_tilde,
                             Z_tilde_gamma_cols,
                             P_tilde,
                             gamma_tilde){

  mu_deriv <- sapply(1:J, function(j)
    t(X[i,k,drop = F])%*%(Z[i,,drop = F]%*%P[,j,drop = F]*exp(gammas[i] +
                                                                X[i,,drop = F]%*%B[,j,drop = F])))

  K_tilde <- dim(P_tilde)[1]
  for(k_tilde in 1:K_tilde){
    if(k_tilde %in% Z_tilde_gamma_cols){
      mu_deriv <- mu_deriv + sapply(1:J, function(j)
        exp(gammas[i])*
          (Z_tilde[i,k_tilde,drop = F])%*%
          P_tilde[k_tilde,j,drop = F]*
          exp(gamma_tilde[k_tilde] +
                X_tilde[k_tilde,,drop = F]%*%B[,j,drop = F])*
          X_tilde[k_tilde,k,drop = F])
    } else{
      mu_deriv <- mu_deriv +
        sapply(1:J, function(j) (Z_tilde[i,k_tilde,drop = F])%*%
                 P_tilde[k_tilde,j,drop = F]*
                 exp(gamma_tilde[k_tilde] +
                       X_tilde[k_tilde,,drop = F]%*%B[,j,drop = F])*
                 X_tilde[k_tilde,k,drop = F])
    }
  }



  return(mu_deriv)
}