Prof. Ram Shanmugam

Texas State University at San Marcos, USA

E-mail: rs25@txstate.edu

Qualifications

1979 Ph. D., Temple University, Philadelphia, PA, USA

1974 M.S., Rensselaer Polytechnic, Troy, NY, USA

1973 M.S., Brigham Young University, Provo, UT, USA

1967 M.Sc., University of Madras, Chennai, India

1965 B.Sc., University of Madras, Chennai, USA

Publications (Selected)

1. Shanmugam, R. (2014) A bivariate probability model to identify “honesty” versus “cheating” in economic surveys: Xenophobia is illustrated. Am. J. Econ. Bus. Admin., 6: 42-48.
2. Shanmugam, R. (2014) C(∝) method to check daunting over/under variances to understand times to aftershocks since a major earthquake, Computer, Electronics, Electrical, and Communication, 59, 190-193.
3. Shanmugam, R. (2014). Data guided public healthcare decision-making, Volume II, Category: Medicare and Healthcare Administration, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 30-43.
4. Shanmugam, R. (2014). Data envelopment analysis for operational efficiency, Volume II, Category: Data Envelopment Analysis, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 18-28.
5. Shanmugam, R. (2014). Stochastic frontier analysis and cancer survivability, Volume V, Category: Stochastic Models, Encyclopedia of Business Analytics and Optimization, edited by John Wang. pp. 18-26.
6. Shanmugam, R. (2014). Over/under dispersion sometimes necessitates modifying, International Journal of Statistics and Poisson model with illustration of tetanus cases and deaths after tsunami, International Journal of Ecological Economics & Statistics, 34(3), 37-42.
7. Shanmugam, R. (2014). Revelation of shrunken or stretched binomial dispersion and public perception of situations which might spread AIDS or HIV, accepted to appear in International Journal of Research in Medical Sciences, 2(2), 462-467.
8. Shanmugam, R. (2014). Tweaked binomial distribution to capture the impact of drilling to cure bioterror victims in hospitals, International Journal of Statistics and Economics, 13(1), 40-45.
9. Shanmugam, R. (2014). An assessment of nurses’ sufficient immunity when treating infectious patients using bumped-up binomial model, International Journal of Research in Medical Sciences, 2(1), 132-138.
10. Zhang, Y., Singh, J. and Shanmugam, R. (2014). Modeling to capture covariate effect, accepted to appear in Communications in Statistics, page numbers are pending.

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