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m_lmPredict = function(Matrix[Double] X, Matrix[Double] B, 
  Matrix[Double] ytest, Integer icpt = 0, Boolean verbose = FALSE) 
  return (Matrix[Double] yhat)
{
  intercept = ifelse(icpt>0 | ncol(X)+1==nrow(B), as.scalar(B[nrow(B),]), 0);
  yhat = X %*% B[1:ncol(X),] + intercept;

  if( verbose ) {
    y_residual = ytest - yhat;
    avg_res = sum(y_residual) / nrow(ytest);
    ss_res = sum(y_residual^2);
    ss_avg_res = ss_res - nrow(ytest) * avg_res^2;
    R2 = 1 - ss_res / (sum(ytest^2) - nrow(ytest) * (sum(ytest)/nrow(ytest))^2);
    print("\nAccuracy:" +
          "\n--sum(ytest) = " + sum(ytest) +
          "\n--sum(yhat) = " + sum(yhat) +
          "\n--AVG_RES_Y: " + avg_res +
          "\n--SS_AVG_RES_Y: " + ss_avg_res +
          "\n--R2: " + R2 );
  }
}
