Multivariate Generalized Birnbaum-Saunders Models Applied to Case Studies in Bio-Engineering and Industry
Birnbaum-Saunders models are receiving considerable attention in the literature. Multivariate regression models are a useful tool in the multivariate analysis, which takes into account the correlation between variables. Diagnostic analysis is an important aspect to be considered in the statistical modeling. In this work, we formulate a statistical methodology based on multivariate generalized Birnbaum-Saunders regression models and their diagnostics. We implement the obtained results in the R software, which are illustrated with two real-world multivariate data sets related to case studies in bio-engineering and industry to show their potential applications.
The authors thank the editors and reviewers for their constructive comments on an earlier version of this manuscript. This research work was partially supported by FONDECYT 1160868 grant from the Chilean government.
- 13.Lepadatu, D., Kobi, A., Hambli, R., Barreau, A.: Lifetime multiple response optimization of metal extrusion die. In: Proceedings of Annual Reliability and Maintainability Symposium, pp. 37–42. IEEE, Piscataway (2005)Google Scholar
- 20.Vivanco, J.F., Burgers, T.A., García, S., Crookshank, M., Kunz, M., MacIntyre, N.J., Harrison, M.M., Bryant, J.T., Sellens, R.W., Ploeg, H.L.: Estimating the density of femoral head trabecular bone from hip fracture patients using computed tomography scan data. Proc. Inst. Mech. Eng. H J. Eng. Med. 228, 616–626 (2014)CrossRefGoogle Scholar