Journal of Applied Statistics Best Paper Prize

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Journal of Applied Statistics Best Paper Prize

Journal of Applied Statistics

About the Prize

The Journal of Applied Statistics Best Paper Prize is awarded annually, as decided by the Editor-in-Chief with the support of the Associate Editors. The winning article receives a £500 prize, and their paper will be made free to view for the following year. All articles published in the Journal are automatically included for consideration.

The 2020 Best Paper awarded by the Award Selection Committee is 'Ordered quantile normalization: a semiparametric transformation built for the cross-validation era', by Peterson, Ryan A.; Cavanaugh, Joseph E. The Committee provided the following remarks:

"The authors of this article proposed a new transformation, called the Ordered Quantile (ORQ) normalization, to produce normally distributed data that follow any arbitrary distribution. Extensive simulation studies were conducted for the cases where the data were generated from known distributions of the asymmetry, bimodal and heavy-tailed types. The effectiveness of the ORQ technique was compared with other popular normalization methods. The proposed normalization transformation guarantees, in the absence of ties, to produce normally distributed transformed data that is related one-to-one with the original data. The proposed method is also incorporated in an R package (best Normalize) to facilitate its use. Such a technique is very useful, especially in an unsupervised machine learning framework, which often requires normally distributed data."

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Year Author(s) Article Volume Issue
2020 - Winner Ryan A. Peterson & Joseph E. Cavanaugh Ordered quantile normalization: a semiparametric transformation built for the cross-validation era 47 13-15
2019 - Winner Cheng Ju et al. Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods 46 12
2019 - Winner J. Pecanka, A. W. van der Vaart & M. A. Jonker Modeling association between multivariate correlated outcomes and high-dimensional sparse covariates: the adaptive SVS method 46 5
2019 - Highly Commended Marcelo Bourguignon, Josemar Rodrigues & Manoel Santos-Neto Extended Poisson INAR(1) processes with equidispersion, underdispersion and overdispersion 46 1
2019 - Highly Commended Antonio Punzo A new look at the inverse Gaussian distribution with applications to insurance and economic data 46 7
2018 - Winner Georgiana Onicescu et al. Spatially explicit survival modeling for small area cancer data 45 3
2018 - Highly Commended Cheng Ju, Aurélien Bibaut, Mark van der Laan The relative performance of ensemble methods with deep convolutional neural networks for image classification 45 15
2018 - Highly Commended Matioli, L. C.; Santos, S. R.; Kleina, M.; Leite, E. A. A new algorithm for clustering based on kernel density estimation 45 2
2017-Highly Commended Chen Peng, Maochao Xu, Shouhuai Xu & Taizhong Hu Modeling and predicting extreme cyber attack rates via marked point processes 44 14
2017-Highly Commended Daniel McNeish Missing data methods for arbitrary missingness with small samples 44 1

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