Peyton Cook, PhD

Peyton Cook, PhD
Associate Professor of Mathematics
College of Engineering & Natural Sciences
Mathematics
918-631-2991 Keplinger Hall Room 3215

Education

PhD – Oklahoma State University MS – Oklahoma State University BS – Oklahoma State University BA – The University of Tulsa

Bio

Peyton Cook received his Ph.D. in Statistics from Oklahoma State University in 1983. He has published papers on the theory of Bayesian Statistical Inference as well as papers applying statistics to business and biology. His current interest is Henstock-Kurzweil integration.

Research Interests

Bayesian Statistical Inference
ARIMA time series
Financial mathematics and numerical solutions to Ito Processes
Econometrics
Generalized Riemann Integration

Teaching Interests

Statistics Methods for Engineers and Scientists
Ordinary Differential Equations
Calculus II, Integration and Series
Box-Jenkins Time Series Forecasting
Generalized Linear Models
Probability for Actuaries
Basic Calculus

Publications

Journal Articles

  • Sanderson, Charlotte E., Peyton Cook, Peggy S. M. Hill, Benjamin S. Orozco, Harrington Wells and Charles I. Abramson. 2013. Nectar quality perception by honey bees (Apis mellifera ligustica). Journal of Comparative Psychology 127: 341-251. DOI:10.1037/a0032613

  • Cook, P, C. Fu, M. Hickey, E. Han, and K. S. Miller (2004), “SAS programs for real-time RT-PCR having multiple independent samples”, BioTechniques 37, pp. 990-995

  • Marino, J. H., P. Cook, and K. S. Miller (2003), “Accurate and statistically verified quantification of relative mRNA abundances using SYBR Green I and real-time RT-PCR”, Journal of Immunological Methods, 283, pp. 291-306

  • Cakmak, I., Cook, P., Hollis, J., Shah, N., Huntley, D., Van Valkenburg, D., and H. Wells (1999), “Africanized Honey Bee Response to Differences in Reward Frequency”, Journal of Apicultural Research, 38(3-4), pp. 125-136

  • Wells, H., Cakmak, I, Cook, P., and D. Van Valkenburg (1998), “Alternative Africanization Models for the Yucatan: Continued Discussion”, Bee World, pp. 106-111

  • Broemeling, L. D. and P. Cook (1997), “A Bayesian Analysis of Regression Models with Continuous Errors with Application to Longitudinal Studies”, Statistics in Medicine, 16, pp. 321-332

  • Cook, P. and L. D. Broemeling (1995), “Bayesian Statistics with Mathematica”, The American Statistician, Vol. 49, No. 1, pp. 70-76

  • Cook, P. and L. D. Broemeling (1994), “A Bayesian WLS Approach to Generalized Linear Models”, Communications in Statistics, 23(12), pp. 3323-3347

  • Cook, P. and L. D. Broemeling (1993), “Bayesian Estimation of the Mean of an Autoregressive Process”, The Journal of Applied Statistics, 20(1), pp. 25-39

  • Broemeling, L. D. and P. Cook (1992), “Bayesian Analysis of Threshold Autoregressions”, Communications in Statistics, 21(9), pp. 2459-2482

  • Broemeling, L.D., Cook, P., and M. Gharraf (1990), “A Bayesian Analysis of the Mixed Linear Model”, Communications in Statistics, A19(3), pp. 987-1002

  • Wells, H. Wells, P. H., and P. Cook (1989), “The Importance of Overwinter Aggregation for Reproductive Success of Monarch Butterflies (anaus plexippus)”, The Journal of Theoretical Biology, pp. 115-131

  • Cook, Peyton J. (1987), “Bayesian Autoregressive Filter and Squared Gain Estimation”, Communications in Statistics, 16(9), pp. 2697-2715

  • Cook, Peyton (1985), “Bayesian Autoregressive Spectral Analysis”, Communications in Statistics, A14(5), pp. 1001-1018

  • Berberet, R.D., Cook, P.J., and D. A. Sander (1982), “Fecundity of the Lesser Cornstalk Borer, Elasmopalpus lignosellus, from Florunner and Spanhoma Peanut Cultivars”, Peanut Science, 9, pp. 60-62. Also listed as Journal Article 4118 of the Agric. Exp. Station, Okla. State Univ, Stillwater, Okla.

Conference Proceedings

  • Pomeranz, S., and P. Cook. My Fifty Years of Calculus. ASEE: 2017 American Society for Engineering Education Annual Conference Proceedings, 2017.
  • Letcher, J. H., O’Neil, K. A., and P. Cook (1993), “An Imaging Device that Uses the Wavelet Transformation as the Image Reconstruction Algorithm: Part III”, Proceedings of the IEE, UK., Acoustic Sensing and Imaging, 29-30 March 1993, pp. 56-59

  • Cook, P., Broemeling, L., and M. Gharraf (1990), “Using a Mixed Model Analysis to Improve the Manufacturing Process”” Proceedings of the First Oklahoma Quality Conference, Stillwater, Oklahoma, pp. 50-63

  • Broemeling, L. D. and P. Cook (1988), “Bayesian Forecasting”, contained in The American Statistical Association 1988 Proceedings of the Business and Economic Statistics Section, pp. 590-595

Book Chapters

  • Cook, P. and L. D. Broemeling (1996), “Analyzing Threshold Autoregressions with a Bayesian Approach”, in Advances in Econometrics: Bayesian Methods Applied to Time Series Data, Vol. 11B, pp. 89-107, JAI Press, Inc., Greenwich, Connecticut

  • Broemeling, L. D., Cook, P., and J. Chin Choy (1991), “Bayesian Inferences about the Intersection of Two Regressions”, Chapter 6, pp. 77-84, in Economic Structural change:Analysis and Forecasting, edited by Hackl and Westlund, Springer-Verlag

  • Cook, Peyton J. (1988), “Small Sample Bayesian Frequency Domain Analysis of Autoregressive Models”, Chapter 5 in Bayesian Analysis of Time Series and Dynamic Models, pp. 101-126, edited by James C. Spall, Marcel Dekker, New York

Courses Taught

  • Statistical Methods for Scientists and Engineers
  • Mathematical Statistics
  • Differential Equations