https://orcid.org/0000-0001-6270-3842
References
- Andrews, L. C. 1997. Special functions of mathematics for engineers. 2nd ed. Bellingham, WA: SPIE–The International Society for Optical Engineering.
- Arnold, T. 2013. dgof: Discrete goodness-of-fit tests. R package version 1.2. https://www.rdocumentation.org/packages/dgof/versions/1.2 (accessed February 20, 2020).
- Betensky, R. A. 2019. The p-value requires context, not a threshold. The American Statistician 73 (sup1):115–17. doi: 10.1080/00031305.2018.1529624.
- Casella, G., and R. L. Berger. 2001. Statistical inference. 2nd ed. Pacific Grove, CA: Cengage Learning.
- Chen, M., S. Mao, and Y. Liu. 2014. Big data: A survey. Mobile Networks and Applications 19 (2):171–209. doi: 10.1007/s11036-013-0489-0.
- Cohen, J. 1992. A power primer. Psychological Bulletin 112 (1):155–59. 1.155. doi: 10.1037/0033-2909.112.
- Dodge, Y. 2008. The concise encyclopedia of statistics. New York: Springer-Verlag.
- Fan, J., F. Han, and H. Liu. 2014. Challenges of big data analysis. National Science Review 1 (2):293–314. doi: 10.1093/nsr/nwt032.
- Greenland, S. 2019. Valid P-values behave exactly as they should: Some misleading criticisms of p values and their resolution with S-values. The American Statistician 73 (sup1):106–14. doi: 10.1080/00031305.2018.1529625.
- Havlicek, L. L., and N. L. Peterson. 1974. Robustness of the T test: A guide for researchers on effect of violations of assumptions. Psychological Reports 34 (3_suppl):1095–114. doi: 10.2466/pr0.1974.34.3c.1095.
- Kettenring, J. R. 2009. Massive datasets. Wiley Interdisciplinary Reviews: Computational Statistics 1 (1):25–32. doi: 10.1002/wics.15.
- Krawczyk, B. 2016. Learning from imbalanced data: Open challenges and future directions. Progress in Artificial Intelligence 5 (4):221–32. doi: 10.1007/s13748-016-0094-0.
- Marsaglia, G., W. W. Tsang, and J. Wang. 2003. Evaluating Kolmogorov’s distribution. Journal of Statistical Software 8 (18):1–4. doi: 10.18637/jss.v008.i18.
- R Core Team. 2013. stats: The R stats package. R package version 3.6.2. https://www.rdocumentation.org/packages/stats/versions/3.6.2 (accessed February 20, 2020).
- Seber, G. 2015. The linear model and hypothesis: A general unifying theory. Cham, Switzerland: Springer International Publishing.
- van der Vaart, A. W. 2012. Asymptotic statistics. Cambridge, UK: Cambridge University Press.
- Wasserstein, R. L., A. L. Schirm, and N. A. Lazar. 2019. Moving to a world beyond ‘p < 0.05. The American Statistician 73 (sup1):1–19. doi: 10.1080/00031305.2019.1583913.