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CONTRIBUTIONS TO ESTIMATION AND MODELING USING QUANTILES

Part of: Multivariate analysis Distribution theory - Probability

Published online by Cambridge University Press:  21 September 2020

DILANKA SHENAL DEDDUWAKUMARA Open the ORCID record for DILANKA SHENAL DEDDUWAKUMARA [Opens in a new window]
DILANKA SHENAL DEDDUWAKUMARA*
Affiliation:
Department of Mathematics and Statistics, La Trobe University, Bundoora, Victoria3086, Australia
*
e-mail: [email protected]
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Abstract

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Keywords

quartile estimationgeneralised lambda distributiongrouped dataquartile-based inequality measures

MSC classification

Primary: 62H12: Estimation
Secondary: 60E05: Distributions
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 103 , Issue 3 , June 2021 , pp. 523 - 524
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Copyright
© 2020 Australian Mathematical Publishing Association Inc.

Footnotes

Thesis submitted to La Trobe University in February 2020; degree approved on 11 March 2020; supervisors Luke Prendergast and Bob Staudte.

References

Dedduwakumara, D. S. and Prendergast, L. A., ‘Interval estimators for inequality measures using grouped data’, in: Statistics and Data Science, Proceedings of the Research School on Statistics and Data Science 2019 (Springer, Singapore, 2019), 238–252.Google Scholar
Dedduwakumara, D. S. and Prendergast, L. A., ‘Confidence intervals for quantiles from histograms and other grouped data’, Commun. Stat. Simul. Comput. 49(6) (2020), 1546–1559.CrossRefGoogle Scholar
Dedduwakumara, D. S., Prendergast, L. A. and Staudte, R. G., ‘A simple and efficient method for finding the closest generalized lambda distribution to a specific model’, Cogent Math. Stat. 6(1) (2019), 1602929. CrossRefGoogle Scholar
Dedduwakumara, D. S., Prendergast, L. A. and Staudte, R. G., ‘An efficient estimator of the parameters of the generalized lambda distribution’, J. Stat. Comput. Simul. Published online (21 August 2020), 19 pages.Google Scholar