Simulation-based estimation for correlated cost elements

In this paper, we present a general method to incorporate correlations between cost elements in the process of cost estimation. The proposed method first checks the feasibility of the correlation (Pearson or Spearman) matrix, adjusts it if necessary, then uses the correlations to generate correlated multivariate random vectors, which are employed to model possible outcomes of the cost elements. The method is applied to a full data set of 216 British office buildings to illustrate its practical use. The application result indicates that the impact of correlations is significant and may cause serious problems if neglected. The result is also used to validate that the proposed method can capture the correlations with relatively small deviations.