Now showing items 3-22 of 39

    • 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 ...
    • 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. ...
    • 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 ...
    • Clustering Monitoring Stations Based on Two Rank-Based Criteria of Similarity of Temporal Profiles 

      Farrar, David; Smith, Eric (Virginia Tech, 2006-09)
      To support evaluation of water quality trends, a water quality variable may be measured at a series of points in time, at multiple stations. Summarization of such data and detection of spatiotemporal patterns may benefit ...
    • 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 ...
    • 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 ...
    • Dimension Reduction for Multinomial Models Via a Kolmogorov-Smirnov Measure (KSM) 

      Loftus, Stephen C.; House, Leanna L.; Hughey, 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 ...
    • 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 ...
    • Error Models in Geographic Information Systems Vector Data Using Bayesian Methods 

      Love, Kimberly R.; Ye, Keying; Smith, Eric P.; Prisley, Stephen P. (Virginia Tech, 2007)
      Geographic Information Systems, or GIS, has been an evolving science since its introduction. Recently, many users have become concerned with the incorporation of error analysis into GIS map products. In particular, there ...
    • Evaluating And Interpreting Interactions 

      Hinkelmann, Klaus (Virginia Tech, 2004-12-13)
      The notion of interaction plays an important − and sometimes frightening − role in the analysis and interpretation of results from observational and experimental studies. In general, results are much easier to explain and ...
    • A Finite Mixture Approach for Identification of Geographic Regions with Distinctive Ecological Stressor-Response Relationships 

      Farrar, David; Prins, Samantha C. Bates; Smith, Eric P. (Virginia Tech, 2006)
      We study a model-based clustering procedure that aims to identify geographic regions with distinctive relationships among ecological and environmental variables. We use a finite mixture model with a distinct linear regression ...
    • 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 ...
    • An Improved Genetic Algorithm Using a Directional Search 

      Wan, Wen; Birch, Jeffrey B. (Virginia Tech, 2009)
      The genetic algorithm (GA), a very powerful tool used in optimization, has been applied in various fields including statistics. However, the general GA is usually computationally intensive, often having to perform a large ...
    • 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 ...
    • 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 Investigation of Combinations of Multivariate Shewhart and MEWMA Control Charts for Monitoring the Mean Vector and Covariance Matrix 

      Reynolds, Marion R. Jr.; Stoumbos, Zachary G. (Virginia Tech, 2008-01-22)
      When monitoring a process which has multivariate normal variables, the Shewhart-type control chart (Hotelling (1947)) traditionally used for monitoring the process mean vector is effective for detecting large shifts, but ...
    • Linear Mixed Model Robust Regression 

      Waterman, Megan J.; Birch, Jeffrey B.; Schabenberger, Oliver (Virginia Tech, 2006-11-05)
      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 ...
    • 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, ...
    • Monitoring Markov Dependent Observations with a Log-Likelihood Based CUSUM 

      Mousavi, Shabnam; Reynolds, Marion R. Jr. (Virginia Tech, 2008)
      When control charts are used to monitor a proportion p it is traditionally assumed that the binary observations are independent. The work that has been done on monitoring autocorrelated binary observations has assumed a ...
    • 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 ...