MADUKA RUPASINGHE WEBSITE
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Office: 215 Patterson
Phone: 419 207 6759
Email: mrupasin@ashland.edu
Office hours: MW 12:00 PM - 1:00 PM TTH 1:30 PM - 3:00 PM
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Education
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Research
My main research area is bootstrap methods in Time Series. I am also interested in Survival Analysis and Reliability Theory.
Publications
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Rupasinghe M., Mukhopadhyay P., Samaranayake V.A.; “Obtaining
Predication Intervals for FARIMA processes using Sieve Bootstrap," Journal
of Statistical Computations and Simulations, Accepted Rupasinghe
M., Samaranayake V.A.; “The Asymptotic Properties of Sieve Bootstrap Prediction
Intervals for FARIMA processes,” Statistical and Probability Letters, 2012, 82 2108-2114 Gamagedara S., Kaczmarek A., Jiang,Y.,
Cheng X., Rupasinghe M.; “Validation Study of Urinary metabolites as Potential
Biomarkers for Prostate Cancer Detection,” Bioanalysis, 2012, 4, 1175-118
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Rupasinghe M., Samaranayake V.A.; “Prediction Interval for ARIMA
processes: A Sieve Bootstrap Approach,” 2012 Proceedings of the Joint Statistical Meetings, San Diego,
California Rupasinghe M., Mukhopadhyay P., Samaranayake V.A.; “Obtaining
Predication Intervals for FARIMA processes using Sieve Bootstrap," 2011Proceedings of the Joint Statistical Meetings, Miami,
Florida
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Teaching
- SP13: MATH 208 Elementary Statistics; MATH 202 Calculus II
- FS12: MATH 208 Elementary Statistics; MATH 341 Applied Intermediate Statistics
Teaching Tools developed by me
- If you want to be successful in a math class, you are encouraged go through this presentation.
- Understanding Law of Large Numbers with a simulation: an excel application.
- Understanding sampling distribution of sample mean (Central Limit Theorem) with a simulation: an excel application.
- Understanding confidence intervals with a simulation: an excel application.
- Understanding hypothesis testing with a simulation: an excel application.
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Statistical Consulting
I offer a free statistical consulting service to the AU faculty and
students as a service to the campus community. The areas of specialization
include but are not limited to:
- Multiple Regression Analysis
- Time Series Analysis
- Principal Component Analysis
- Design of Experiments
- ANOVA / MANOVA
- Logistic, Poisson, Negative Binomial Regressions
- Factor Analysis
- Cluster Analysis
- Help with SPSS, MATLAB, R and other statistical softwares.
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Useful Links
Here are some useful links:
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