Now showing items 1-20 of 153

    • High Breakdown Estimation Methods for Phase I Multivariate Control Charts 

      Jensen, Willis A.; Birch, Jeffrey B.; Woodall, William H. (Virginia Tech, 2005)
      The goal of Phase I monitoring of multivariate data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High breakdown estimation ...
    • Robust Parameter Design: A Semi-Parametric Approach 

      Pickle, Stephanie M.; Robinson, Timothy J.; Birch, Jeffrey B.; Anderson-Cook, Christine M. (Virginia Tech, 2005)
      Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels ...
    • Statistical Monitoring of Heteroscedastic Dose-Response Profiles from High-throughput Screening 

      Williams, J.D.; Birch, J.B.; Woodall, W.H.; Ferry, N.M. (Virginia Tech, 2006)
      In pharmaceutical drug discovery and agricultural crop product discovery, in vivo bioassay experiments are used to identify promising compounds for further research. The reproducibility and accuracy of the bioassay is ...
    • A Bayesian Hierarchical Approach to Dual Response Surface Modeling 

      Chen, Younan; Ye, Keying (Virginia Tech, 2005)
      In modern quality engineering, dual response surface methodology is a powerful tool to monitor an industrial process by using both the mean and the standard deviation of the measurements as the responses. The least squares ...
    • Construction Concepts for Continuum Regression 

      Spitzner, Dan J. (Virginia Tech, 2004-08-28)
      Approaches for meaningful regressor construction in the linear prediction problem are investigated in a framework similar to partial least squares and continuum regression, but weighted to allow for intelligent specification ...
    • Dimension Reduction for Multinomial Models Via a Kolmogorov-Smirnov Measure (KSM) 

      Loftus, Stephen C.; House, Leanna L.; Hughley, Myra C.; Walke, Jenifer B.; Becker, Matthew H.; Belden, Lisa K. (Virginia Tech, 2015)
      Due to advances in technology and data collection techniques, the number of measurements often exceeds the number of samples in ecological datasets. As such, standard models that attempt to assess the relationship between ...
    • Speculations Concerning the First Ultraintelligent Machine 

      Good, Irving John (Virginia Tech, 2005-03-05)
      The survival of man depends on the early construction of an ultraintelligent machine. In order to design an ultraintelligent machine we need to understand more about the human brain or human thought or both. In the following ...
    • A Phase I Cluster-Based Method for Analyzing Nonparametric Profiles 

      Chen, Yajuan; Birch, Jeffrey B.; Woodall, William H. (Virginia Tech, 2014)
      A cluster-based method was used by Chen et al.²⁴ to analyze parametric profiles in Phase I of the profile monitoring process. They showed performance advantages in using their cluster-based method of analyzing parametric ...
    • Interaction Analysis of Three Combination Drugs via a Modified Genetic Algorithm 

      Wan, Wen; Pei, Xin-Yan; Grant, Steven; Birch, Jeffrey B.; Felthousen, Jessica; Dai, Yun; Fang, Hong-Bin; Tan, Ming; Sun, Shumei (Virginia Tech, 2014)
      Few articles have been written on analyzing and visualizing three-way interactions between drugs. Although it may be quite straightforward to extend a statistical method from two-drugs to three-drugs, it is hard to visually ...
    • An Improved Hybrid Genetic Algorithm with a New Local Search Procedure 

      Wan, Wen; Birch, Jeffrey B. (Virginia Tech, 2012)
      A hybrid genetic algorithm (HGA) combines a genetic algorithm (GA) with an individual learning procedure. One such learning procedure is a local search technique (LS) used by the GA for refining global solutions. A HGA is ...
    • Effect of Phase I Estimation on Phase II Control Chart Performance with Profile Data 

      Chen, Yajuan; Birch, Jeffrey B.; Woodall, William H. (Virginia Tech, 2014)
      This paper illustrates how Phase I estimators in statistical process control (SPC) can affect the performance of Phase II control charts. The deleterious impact of poor Phase I estimators on the performance of Phase II ...
    • Outlier Robust Nonlinear Mixed Model Estimation 

      Williams, James D.; Birch, Jeffrey B.; Abdel-Salam, Abdel-Salam G. (Virginia Tech, 2014)
      In standard analyses of data well-modeled by a nonlinear mixed model (NLMM), an aberrant observation, either within a cluster, or an entire cluster itself, can greatly distort parameter estimates and subsequent standard ...
    • Cluster-Based Bounded Influence Regression 

      Lawrence, David E.; Birch, Jeffrey B.; Chen, Yajuan (Virginia Tech, 2012)
      A regression methodology is introduced that obtains competitive, robust, efficient, high breakdown regression parameter estimates as well as providing an informative summary regarding possible multiple outlier structure. ...
    • Nonparametric and Semiparametric Linear Mixed Models 

      Waterman, Megan J.; Birch, Jeffrey B.; Abdel-Salam, Abdel-Salam G. (Virginia Tech, 2012)
      Mixed models are powerful tools for the analysis of clustered data and many extensions of the classical linear mixed model with normally distributed response have been established. As with all parametric models, correctness ...
    • Cost Penalized Estimation and Prediction Evaluation for Split-Plot Designs 

      Liang, Li; Anderson-Cook, Christine M.; Robinson, Timothy J. (Virginia Tech, 2005-02-02)
      The use of response surface methods generally begins with a process or system involving a response y that depends on a set of k controllable input variables (factors) x₁, x₂,…,xk. To assess the effects of these factors on ...
    • Statistical Methods for Degradation Data with Dynamic Covariates Information and an Application to Outdoor Weathering Data 

      Hong,Yili; Duan, Yuanyuan; Meeker, William Q.; Stnaley, Deborah L.; Gu, Xiahohong (Virginia Tech, 2012-10-09)
      Degradation data provide a useful resource for obtaining reliability information for some highly reliable products and systems. In addition to product/system degradation measurements, it is common nowadays to dynamically ...
    • Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers 

      Walker, Eric L.; Starnes, B. Alden; Birch, Jeffrey B.; Mays, James E. (American Institute of Aeronautics and Astronautics, 2010)
      This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed byMays, Birch, ...
    • Cluster-Based Profile Monitoring in Phase I Analysis 

      Chen, Yajuan; Birch, Jeffrey B. (Virginia Tech, 2012)
      An innovative profile monitoring methodology is introduced for Phase I analysis. The proposed technique, which is referred to as the cluster-based profile monitoring method, incorporates a cluster analysis phase to aid in ...
    • On Computing the Distribution Function for the Sum of Independent and Non-identical Random Indicators 

      Hong,Yili (Virginia Tech, 2011-04-05)
      The Poisson binomial distribution is the distribution of the sum of independent and non-identical random indicators. Each indicator follows a Bernoulli distribution with individual success probability. When all success ...
    • Nonparametric and Semiparametric Mixed Model Methods for Phase I Profile Monitoring 

      Abdel-Salam, Abdel-Salam G.; Birch, Jeffrey B.; Jensen, Willis A. (Virginia Tech, 2010)
      Profile monitoring is an approach in quality control best used where the process data follow a profile (or curve). The majority of previous studies in profile monitoring focused on the parametric modeling of either linear ...