Citations refer to the original publication, not to a Scieee localized version.
Fehrle, D., Heiberger, C., & Huber, J. (2025). Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models. Computational Economics, 65(2), 1083–1146. https://doi.org/10.1007/s10614-024-10772-5
Fehrle, Daniel, et al. “Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models.” Computational Economics, vol. 65, no. 2, 2025, pp. 1083–1146. https://doi.org/10.1007/s10614-024-10772-5.
Fehrle, Daniel, Christopher Heiberger, and Johannes Huber. “Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models.” Computational Economics 65, no. 2 (2025): 1083–1146. https://doi.org/10.1007/s10614-024-10772-5.
Fehrle, D., Heiberger, C. and Huber, J. (2025) ‘Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models’, Computational Economics, 65(2), pp. 1083–1146. Available at: https://doi.org/10.1007/s10614-024-10772-5.
D. Fehrle, C. Heiberger, and J. Huber, “Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models,” Computational Economics, vol. 65, no. 2, pp. 1083–1146, 2025, doi: 10.1007/s10614-024-10772-5.
@article{fehrle2025polynomial,
author = {Fehrle, Daniel and Heiberger, Christopher and Huber, Johannes},
title = {Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models},
journal = {Computational Economics},
year = {2025},
volume = {65},
number = {2},
pages = {1083--1146},
publisher = {New York, NY: Springer US,New York, NY: Springer US},
doi = {10.1007/s10614-024-10772-5},
url = {https://doi.org/10.1007/s10614-024-10772-5}
}
