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Marion R. Reynolds

Professor Emeritus, 1972-2010
Marion R. Reynolds
mrr@vt.edu

Education

  • Ph.D. (Sequential Nonparametric Statistics), Stanford, 1972
  • M.S., Stanford, 1971
  • B.S., Virginia Tech. 1968

  • Quality control
  • Statistical inference
  • Probability and distribution theory
  • Sequential analysis
  • Engineering statistics

  • Statistical Process Control
  • Sequential Analysis
  • Validation of Simulation Models
  • Applications of Statistics and Operation Research to Natural Resource Problems

  • Stoumbos, Z.G. and M.R. Reynolds, Jr.(2000) Robustness to Non-normality and Autocorrelation of Individuals Control Charts for Monitoring the Process Mean and Variance. Journal of Statistical Computation and Simulation, 66, 145-187.
  • Reynolds, M.R., Jr. and Z.G. Stoumbos (2000). A General Approach to Modeling CUSUM Charts for a Proportion. IIE Transactions, 32, 515-535.
  • Stoumbos, Z.G., M.R. Reynolds, Jr., T.P. Ryan, and W.H. Woodall (2000). The State of Statistical Process Control as We Proceed into the 21st Century. Journal of the American Statistical Association, 95, 992-998.
  • Stoumbos, Z.G. and M.R. Reynolds, Jr.(2001) The SPRT Control Chart for the Process Mean with Samples Starting at Fixed Times. Nonlinear Analysis: Real World Applications, 2, 1-34.
  • Stoumbos, Z.G., L.A. Jones, W.H. Woodall, and M.R. Reynolds, Jr. (2001). On Shewhart-Type Nonparametric Multivariate Control Charts Based on Data Depth. Frontiers in Statistical Quality Control, 6, 207-227.
  • Reynolds, M.R., Jr. and Z.G. Stoumbos (2001). Monitoring a Proportion Using CUSUM and SPRT Control Charts. Frontiers in Statistical Quality Control, 6, 155-175.
  • Reynolds, M.R., Jr. and J. C. Arnold (2001). EWMA Control Charts with Variable sample Sizes and Variable Sampling Intervals. IIE Transactions, 33, 511-530.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2001). Monitoring the Process Mean and Variance Using Individual Observations and Variable Sampling Intervals. Journal of Quality Technology, 33, 181-205.
  • Arnold, J.C. and M.R. Reynolds, Jr. (2001). CUSUM Control Charts with Variable Sample Sizes and Sampling Intervals. Journal of Quality Technology, 33, 66-81.
  • Lu, C.W. and M.R. Reynolds, Jr. (2001). CUSUM Charts for Monitoring An Autocorrelated Processes. Journal of Quality Technology, 33, 316-334.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2001). Individuals Control Schemes for Monitoring the Mean and Variance of Processes Subject to Drifts. Stochastic Analysis and Applications, 19, 863-892.
  • Stoumbos, Z.G., Reynolds, M.R., Jr. and Woodall, W.H. (2003). Control Chart Schemes for Monitoring the Mean and Variance of Processes Subject to Sustained Shifts and Drifts. Handbook of Statistics: Statistics in Industry, 23, eds. C.R. Rao and R. Khattree, Amsterdam, Netherlands: Elsevier Science, 553-571.
  • Stoumbos, Z. G. and Reynolds, M. R., JR. (2004). The Robustness and Performance of CUSUM Control Charts Based on the Double-Exponential and Normal Distributions. Frontiers in Statistical Quality Control, 7, edited by H.-J. Lenz and P.-Th. Wilrich. Springer-Verlag, Heidelberg, Germany, 79-100.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2004). Control Charts and the Optimal Allocation of Sampling Resources. Technometrics, 46 , 200-214.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2004). Should Observations Be Grouped for Effective Process Monitoring? Journal of Quality Technology, 36, 343-366.
  • Reynolds, M.R., Jr. and Kim, K. (2005). Multivariate Monitoring of the Process Mean Vector With Sequential Sampling. Journal of Quality Technology, 37, 149-162.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2005). Should Exponentially Weighted Moving Average and Cumulative Sum Charts be Used With Shewhart Limits? Technometrics, 47, 409-424.
  • Stoumbos, Z.G. and M.R. Reynolds, Jr. (2005). Economic Statistical Design of Adaptive Control Schemes for Monitoring the Process Mean and Variance: An Application to Analyzers. Nonlinear Analysis: Real World Applications, 6, 817-844.
  • Kim, K. and Reynolds, M.R., Jr. (2005). Multivariate Monitoring Using an MEWMA Control Chart with Unequal Sample Sizes. Journal of Quality Technology, 37, 267-281.
  • Reynolds, M.R., Jr. and Cho, G.Y. (2006). Multivariate Control Charts for Monitoring the Mean Vector and Covariance Matrix. Journal of Quality Technology, 38, 230-253.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2006). Comparisons of Some Exponentially Weighted Moving Average Control Charts for Monitoring the Process Mean and Variance. Technometrics, 48, 550-567.
  • Reynolds, M.R. Jr. and Stoumbos, Z.G. (2006). Does the Rational Subgroups Concept Provide an Effective Guide to Process Sampling? Frontiers in Intelligent Statistical Quality Control, 8th ed., Lenz, H.J. and Wilrich, P.T., eds., pp. 247-256.
  • Reynolds, M.R., Jr. and Kim, K. (2007). Multivariate Control Charts for Monitoring the Process Mean and Variability Using Sequential Sampling. Sequential Analysis, 26, 283-315. (Invited paper in the special volume of Sequential Analysis in honor of Walter Shewhart.)
  • Sego, L. H., Woodall, W. H., and Reynolds, M. R., Jr. (2007)  A Comparison of Surveillance Methods for Small Incidence Rates. Statistics in Medicine, 27, 1225-1247.
  • Joner, M. D., Woodall, W. H., and Reynolds, M. R., Jr. (2008). Detecting a Rate Increase Using a Bernoulli Scan Statistic. Statistics in Medicine, 27, 2555-2573.
  • Park, C. and Reynolds, M. R., Jr. (2008). Economic Design of an Integrated Process Control Procedure with Repeated Adjustments. Journal of the Korean Statistical Society, 37, 155-174.
  • Joner, M. D., Woodall, W. H., Reynolds, M. R., Jr., and Fricker, R. D. (2008). A One-Sided MEWMA Chart for Health Surveillance. Quality and Reliability Engineering International, 24, 503-518.
  • Jensen, W. A., Bryce, G. R., and Reynolds, M. R., Jr. (2008). Design Issues for Adaptive Control Charts. Quality and Reliability Engineering International, 24, 429-445.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2008). Combinations of Multivariate Shewhart and MEMWA Control Charts for Monitoring the Mean Vector and Covariance Matrix. Journal of Quality Technology, 40, 381-393.
  • Sego, L. H., Reynolds, M. R., Jr., and Woodall, W. H. (2009). Risk-Adjusted Monitoring of Survival Times. Statistics in Medicine, 28, 1386-1401.
  • Mousavi, S. and Reynolds, M.R., Jr. (2009). A CUSUM chart for Monitoring a Proportion with Autocorrelated Binary Observations. Journal of Quality Technology, 41, 401-414.
  • Reynolds, M.R., Jr. and Park, C. (2009). CUSUM Charts for Detecting Special Causes in Integrated Process Control. Quality and Reliability Engineering International, 26, 199-221.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2010). Multivariate Monitoring of the Process Mean and Variability Using Combinations of Multivariate Shewhart and MEMWA Control Charts. Frontiers in Intelligent Statistical Quality Control, 9th ed., Lenz, H.J., Wilrich, P.T., and Schmid, W., eds., pp. 37-54.
  • Reynolds, M.R., Jr. and Lou, J. (2010). An Evaluation of a GLR Control Chart for Monitoring the Process Mean. Journal of Quality Technology, 42, 287-310.
  • Reynolds, M.R., Jr. and Stoumbos, Z.G. (2010). Robustness to Non-Normality of CUSUM Control Charts for Monitoring the Process Mean and Variance. Quality and Reliability Engineering International, 26, 453-473.
  • Reynolds, M.R., Jr. and Cho, G. Y. (2011). Multivariate Monitoring of the Process Mean and Variability With Variable Sampling Intervals. Sequential Analysis, 30, 1-40.
  • Huang, W., Reynolds, M.R., Jr. and Wang, S. (2012). A Binomial GLR Control Chart for Monitoring a Proportion. Journal of Quality Technology, in press. 
  • Wang, S. and Reynolds, M.R., Jr. (2012). A GLR Control Chart for Monitoring the Mean Vector of a Multivariate Normal Process.  Journal of Quality Technology, in press.
  • Huang, W., Wang, S. and Reynolds, M.R., Jr. (2012). A Generalized Likelihood Ratio Chart for Monitoring Bernoulli Processes. Quality and Reliability Engineering International, in press. 
  • Xu, L., Wang, S., Peng, Y., Morgan, J. P., Reynolds, M.R., Jr., and Woodall, W. H. (2012). The Monitoring of Linear Profiles with a GLR Control Chart. Journal of Quality Technology, 44, 348-362.
  • Xu, L., Wang, S., and Reynolds, M.R., Jr. (2012). A Generalized Likelihood Ratio Control Chart for Monitoring the Process Mean Subject to Linear Drifts. Quality and Reliability Engineering International, in press. 
  • Reynolds, M.R., Jr. (2012). The Bernoulli CUSUM Chart for Detecting Decreases in a Proportion. Quality and Reliability Engineering International, in press. 
  • Reynolds, M.R., Jr. and Lou, J. (2012). A GLR Control Chart for Monitoring the Process Variance. Frontiers in Intelligent Statistical Quality Control, 10th ed., Lenz, H.J., Schmid, W., and Wilrich, P.T., eds., pp. 3-17.
  • Lou, J., and Reynolds, M. R., Jr. (2012). Maximum-Likelihood Based Diagnostics after a Signal from Control Charts. Journal of Quality Technology, 44, 321-347.
  • Reynolds, M.R., Jr., Lou, J., Lee, J., and Wang, S. (2012). The Design of GLR Control Charts for Monitoring the Process Mean and Variance. Journal of Quality Technology, in press.

 

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