MADUKA RUPASINGHE WEBSITE
Assistant Professor of Mathematics
Ashland University, Ashland OH 44805

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


Education


Research

My main research area is bootstrap methods in Time Series. I am also interested in Survival Analysis and Reliability Theory.

Publications
  • Peer reviewed
  1. Rupasinghe M.; “Sieve Bootstrap Prediction Intervals for Time Series with GARCH Errors,” submitted to Communications in Statistics – Simulation and Computation

  2. Weidenhamer J., Mohney BK., Shihada N., Rupasinghe M.; “Spatial and Temporal Dynamics of Root Exudation: How important is Heterogeneity in Allelopathic interaction?,” Journal of Chemical Ecology, 2014, 40 (8), 940-952

  3. Rupasinghe M., Mukhopadhyay P., Samaranayake V.A.; “Obtaining Predication Intervals for FARIMA processes using Sieve Bootstrap," Journal of Statistical Computations and Simulations, 2014
  4. Rupasinghe M., Samaranayake V.A.; “The Asymptotic Properties of Sieve Bootstrap Prediction Intervals for FARIMA processes,” Statistical and Probability Letters, 2012, 82 2108-2114

  5. 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

  • Preceedings
  1. Rupasinghe M., Samaranayake V.A.; “Prediction Interval for ARIMA processes: A Sieve Bootstrap Approach,” 2012 Proceedings of the Joint Statistical Meetings, San Diego, California

  2. Rupasinghe M., Mukhopadhyay P., Samaranayake V.A.; “Obtaining Predication Intervals for FARIMA processes using Sieve Bootstrap," 2011Proceedings of the Joint Statistical Meetings, Miami, Florida

Teaching
  • FS14:MATH341 Applied Regression Analysis; MATH 201 Applied Calculus; MATH 208 Elementary Statistics; MATH 450 Math seminar
  • SM14: MATH 201 Applied Calculus I; MATH 202 Applied Calculus II
  • SP14: MATH 208 Elementary Statistics; MATH 318 Mathematical Statistics
  • FS13: MATH 208 Elementary Statistics; MATH 317 Probability
  • 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.


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.

Useful Links

Here are some useful links: