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Professor Peter Hall
ACEMS Inaugural Director
The University of Melbourne
Peter Gavin Hall AO FAA FRS (20 November 1951 – 9 January 2016) was an Australian researcher in probability theory and mathematical statistics.
Projects
Publications
Book Chapters
Hall, P.
(2016). Contributions of Rabi Bhattacharya to the Central Limit Theory and Normal Approximation. .
(Denker, M., & Waymire E. C., Ed.).Rabi N. Bhattacharya: Selected Papers. 3-13. doi: 10.1007/978-3-319-30190-7_1
Invited talks, refereed proceedings and other conference outputs
Huang, W., Delaigle A., Hall P., & Kneip A.
(2021). Estimating the covariance of fragmented and other related types of functional data.
4th International Conference on Econometrics and Statistics (EcoSta 2021).
Journal Articles
Doosti, H., & Hall P.
(2016). Making a non-parametric density estimator more attractive, and more accurate, by data perturbation.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(2), 445-462. doi: 10.1111/rssb.12120
Claeskens, G., Dette H., Gijbels I., & Hall P.
(2016). New developments in functional and highly multivariate statistical methodology.
Oberwolfach Reports. 13(1), 567-614. doi: 10.4171/OWR/2016/12
Chen, F., & Hall P.
(2016). Nonparametric estimation for self-exciting point processes—A parsimonious approach.
Journal of Computational and Graphical Statistics. 25(1), 209-224. doi: 10.1080/10618600.2014.1001491
Delaigle, A., Hall P., & Zhou W-X.
(2016). Nonparametric covariate-adjusted regression.
The Annals of Statistics. 44(5), 2190-2220. doi: 10.1214/16-AOS1442
Hall, P., & Hooker G.
(2016). Truncated linear models for functional data.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(3), 637-653. doi: 10.1111/rssb.12125
Delaigle, A., & Hall P.
(2016). Methodology for non-parametric deconvolution when the error distribution is unknown.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(1), 231-252. doi: 10.1111/rssb.12109
Genton, M. G., & Hall P.
(2016). A tilting approach to ranking influence.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 78(1), 77-97. doi: 10.1111/rssb.12102
Chang, J., & Hall P.
(2015). Double-bootstrap methods that use a single double-bootstrap simulation.
Biometrika. 102(1), 203-214. doi: 10.1093/biomet/asu060
Xue, J-H., & Hall P.
(2015). Why Does Rebalancing Class-Unbalanced Data Improve AUC for Linear Discriminant Analysis?.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(5), 1109-1112. doi: 10.1109/TPAMI.2014.2359660
Hall, P., & Racine J. S.
(2015). Infinite order cross-validated local polynomial regression.
Journal of Econometrics. 185(2), 510-525. doi: 10.1016/j.jeconom.2014.06.003
Ferraty, F., & Hall P.
(2015). An Algorithm for Nonlinear, Nonparametric Model Choice and Prediction.
Journal of Computational and Graphical Statistics. 24(3), 695-714. doi: 10.1080/10618600.2014.936605
Delaigle, A., Hall P., & Jamshidi F.
(2015). Confidence bands in non-parametric errors-in-variables regression.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 77(1), 149-169. doi: 10.1111/rssb.12067
Hall, P., & Ma Y.
(2014). Quick and easy one-step parameter estimation in differential equations.
Journal of the Royal Statistical Society: Series B (Statistical Methodology). 76(4), 735-748. doi: 10.1111/rssb.12040
Hall, P., Jin J., & Miller H.
(2014). Feature selection when there are many influential features.
Bernoulli. 20(3), 1647-1671. doi: 10.3150/13-BEJ536