School of Mathematical Sciences
Faculty of Engineering, Computer and Mathematical Sciences
My research developments aim to contribute to the field of quantile-based methods in modelling and estimation. These new methods, have applications in fields such as economics and the health sciences, and also address significant issues related to the wider scientific research community. I have recently completed my PhD in Statistics with several first-author publications in this field of Robust Statistics.
Year Citation 2021 Dedduwakumara, D. S., Prendergast, L. A., & Staudte, R. G. (2021). An efficient estimator of the parameters of the generalized lambda distribution. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 91(1), 197-215.
2020 Dedduwakumara, D. (2020). Contributions to Estimation and Modeling Using Quantiles. Bulletin of the Australian Mathematical Society, 103(3), 523-524.
2019 Dedduwakumara, D. S., Prendergast, L. A., & Robert, G. S. (2019). A simple and efficient method for finding the closest generalized lambda distribution to a specific model. Cogent Mathematics & Statistics, 6(1), 1-11.
2018 Dedduwakumara, D. S., & Prendergast, L. A. (2018). Confidence intervals for quantiles from histograms and other grouped data. Communications in Statistics: Simulation and Computation, 49(6), 1546-1559.
DOI Scopus3 WoS1
— Dedduwakumara, D. S., Prendergast, L. A., & Staudte, R. G. (n.d.). Insights and inference for the proportion below the relative poverty
Year Citation 2019 Dedduwakumara, D. S., & Prendergast, L. A. (2019). Interval Estimators for Inequality Measures Using Grouped Data. In Communications in Computer and Information Science Vol. 1150 CCIS (pp. 238-252). Singapore: Springer.
Statistical Practice I
Statistics and Numerical Methods II
Advanced Mathematical Perspectives II
Connect With Me