Yong Wang

Office: 303S.271 (Maths/Physics Building, Science Centre)
Phone: +64 9 3737599 ext. 84700
E-mail: yongwang AT auckland.ac.nz

Selected Publications

• Xu, D. and Wang, Y. (2023). Density estimation for toroidal data using semiparametric mixtures. Statistics and Computing, (Accepted).
• Xu, D. and Wang, Y. (2023). Density estimation for spherical data using nonparametric mixtures. Computational Statistics & Data Analysis, (Accepted).
• Xue, X. and Wang, Y. (2023). A nonparametric mixture approach to density and null proportion estimation in large-scale multiple comparison problems. Australia & New Zealand Journal of Statistics, (Accepted).
• Hu, S. and Wang, Y. (2021). Modal clustering using semiparametric mixtures and mode flattening. Statistics and Computing, 31, 5, DOI: 10.1007/s11222-020-09985-z.
• Xu, D. and Wang, Y. (2020). Area-proportional visualization for circular data. Journal of Computational and Graphical Statistics, 29, 351-357.
• Wang, Y. and Wang, X. (2019). Classification using semiparametric mixtures. Journal of Applied Statistics, 46, 2056-2074.
• Wang, Y. (2018). Computation of the nonparametric maximum likelihood estimate of a univariate log-concave density. Wiley Interdisciplinary Reviews: Computational Statistics, e1452.
• Liu, Y. and Wang, Y. (2018). A fast algorithm for univariate log-concave density estimation. Australia & New Zealand Journal of Statistics, 60, 258-275.
• Wang, Y. and Fani, S. (2018). Nonparametric maximum likelihood computation of a U-shaped hazard function. Statistics and Computing, 28, 187-200.
• Chee, C.-S. and Wang, Y. (2016). Nonparametric estimation of species richness using discrete k-monotone distributions. Computational Statistics & Data Analysis, 93, 107-118.
• Wang, X. and Wang, Y. (2015). Nonparametric multivariate density estimation using mixtures. Statistics and Computing, 25, 349-364.
• Chee, C.-S. and Wang, Y. (2014). Least squares estimation of a k-monotone density function. Computational Statistics & Data Analysis, 74, 209-216.
• Wang, Y. and Taylor, S. M. (2013). Efficient computation of nonparametric survival functions via a hierarchical mixture formulation. Statistics and Computing, 23, 713-725.
• Chee, C.-S. and Wang, Y. (2013). Estimation of finite mixtures with symmetric components. Statistics and Computing, 23, 233-249.
• Chee, C.-S. and Wang, Y. (2013). Minimum quadratic distance density estimation using nonparametric mixtures. Computational Statistics & Data Analysis, 57, 1-16.
• Wang, Y. (2012). Gauss-Newton method. Wiley Interdisciplinary Reviews: Computational Statistics, 4, 415-420.
• Wang, Y., Ziedins, I., Holmes, M. and Challands, N. (2012). Tree models for difference and change detection in a complex environment. Annals of Applied Statistics, 6, 1162-1184.
• Wang, Y. and Chee, C.-S. (2012). Density estimation using nonparametric and semiparametric mixtures. Statistical Modelling: An International Journal, 12, 67-92.
• Blagojevic, R., Plimmer, B., Grundy, J. and Wang, Y. (2011). Using data mining for digital ink recognition: Dividing text and shapes in sketched diagrams. Computers & Graphics, 35, 976-991.
• Böhning, D. and Wang, Y. (2010) Comments on "Maximum likelihood estimation of a multivariate log-concave density" by Cule, Samworth and Stewart. Journal of the Royal Statistical Society, Series B, 72, 589-590.
• Wang, Y. (2010). Fisher scoring: an interpolation family and its Monte Carlo implementations. Computational Statistics & Data Analysis, 54, 1744-1755.
• Wang, Y. (2010). Maximum likelihood computation for fitting semiparametric mixture models. Statistics and Computing, 20, 75-86.
• Blagojevic, R., Plimmer, B., Grundy, J. and Wang, Y. (2010). Building digital ink recognizers using data mining: Distinguishing between text and shapes in hand drawn diagrams. Lecture Notes in Computer Science, 6096, 358-367.
• Wang, Y. (2009). The constrained Fisher scoring method for maximum likelihood computation of a nonparametric mixing distribution. Computational Statistics, 24, 67-81.
• Wang, Y. (2008). Dimension-reduced nonparametric maximum likelihood computation for interval-censored data. Computational Statistics & Data Analysis, 52, 2388-2402.
• Blagojevic, R., Plimmer, B., Grundy, J. and Wang, Y. (2008). Development of techniques for sketched diagram recognition. Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing, 258-259.
• Wang, Y. (2007). Minimum disparity computation via the iteratively reweighted least integrated squares algorithms. Computational Statistics & Data Analysis, 51, 5662-5672.
• Wang, Y. (2007). Maximum likelihood computation based on the Fisher scoring and Gauss-Newton quadratic approximations. Computational Statistics & Data Analysis, 51, 3776-3787.
• Wang, Y. (2007). On fast computation of the non-parametric maximum likelihood estimate of a mixing distribution. Journal of the Royal Statistical Society, Series B, 69, 185-198.
• Wang, Y. and Witten, I. H. (2002). Modeling for optimal probability prediction. Proceedings of the Nineteenth International Conference on Machine Learning, 650-657. Morgan Kaufmann.
• Frank, E., Wang, Y., Inglis, S., Holmes, G. and Witten, I. H. (1998). Using model trees for classification. Machine Learning, 32, 63-76.

R Packages

• cplots: Plots for Circular Data (version 0.5-0-0).
• cnmlcd: Maximum Likelihood Estimation of a Log-Concave Density Function (version 1.2-0).
• lsei: Solving Least Squares Problems under Equality/Inequality Constraints (version 1.2-0)
• npsurv: Non-Parametric Survival Analysis (version 0.4-0)
• nspmix: Nonparametric and Semiparametric Mixture Estimation (version 1.4-0)