@article{jeong_lu_zhou_ghosh_2007, title={Data-reduction method for spatial data using a structured wavelet model}, volume={45}, ISSN={["0020-7543"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-34247605442&partnerID=MN8TOARS}, DOI={10.1080/00207540600793547}, abstractNote={Recent advances in sensor instrumentation have provided opportunities for process engineers to collect data at various process steps in order to detect process problems and develop remedial procedures. This article presents a structured wavelet model for the reduction of two-dimensional data having distinct structures. The wavelet component of our model can handle irregular data patterns exhibiting many peaks and valleys, while the existence of a distinct data structure prompts the use of polynomial functions on wavelet coefficients. The two-dimensional antenna data is reduced with a structured wavelet model followed by some procedures for the detection of process defects based on the reduced-size data. A real-life example is presented to illustrate the usefulness of the proposed tools in detecting process problems from a potentially large volume of data exhibiting many peaks and valleys.}, number={10}, journal={INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH}, author={Jeong, Myong K. and Lu, Jye-Chyi and Zhou, Weixin and Ghosh, Sujit K.}, year={2007}, pages={2295–2311} }
 @article{ghosh_mukhopadhyay_lu_2006, title={Bayesian analysis of zero-inflated regression models}, volume={136}, ISSN={["0378-3758"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-29444448265&partnerID=MN8TOARS}, DOI={10.1016/j.jspi.2004.10.008}, abstractNote={In modeling defect counts collected from an established manufacturing processes, there are usually a relatively large number of zeros (non-defects). The commonly used models such as Poisson or Geometric distributions can underestimate the zero-defect probability and hence make it difficult to identify significant covariate effects to improve production quality. This article introduces a flexible class of zero inflated models which includes other familiar models such as the Zero Inflated Poisson (ZIP) models, as special cases. A Bayesian estimation method is developed as an alternative to traditionally used maximum likelihood based methods to analyze such data. Simulation studies show that the proposed method has better finite sample performance than the classical method with tighter interval estimates and better coverage probabilities. A real-life data set is analyzed to illustrate the practicability of the proposed method easily implemented using WinBUGS.}, number={4}, journal={JOURNAL OF STATISTICAL PLANNING AND INFERENCE}, author={Ghosh, SK and Mukhopadhyay, P and Lu, JC}, year={2006}, month={Apr}, pages={1360–1375} }
 @article{chen_lu_huo_yin_2001, title={Optimum percentile estimating equations for nonlinear random coefficient models}, volume={97}, ISSN={["0378-3758"]}, DOI={10.1016/S0378-3758(00)00219-6}, abstractNote={In nonlinear random coefficients models, the means or variances of response variables may not exist. In such cases, commonly used estimation procedures, e.g., (extended) least-squares (LS) and quasi-likelihood methods, are not applicable. This article solves this problem by proposing an estimate based on percentile estimating equations (PEE). This method does not require full distribution assumptions and leads to efficient estimates within the class of unbiased estimating equations. By minimizing the asymptotic variance of the PEE estimates, the optimum percentile estimating equations (OPEE) are derived. Several examples including Weibull regression show the flexibility of the PEE estimates. Under certain regularity conditions, the PEE estimates are shown to be strongly consistent and asymptotic normal, and the OPEE estimates have the minimal asymptotic variance. Compared with the parametric maximum likelihood estimates (MLE), the asymptotic efficiency of the OPEE estimates is more than 98%, while the LS-type of procedures can have infinite variances. When the observations have outliers or do not follow the distributions considered in model assumptions, the article shows that OPEE is more robust than the MLE, and the asymptotic efficiency in the model misspecification cases can be above 150%.}, number={2}, journal={JOURNAL OF STATISTICAL PLANNING AND INFERENCE}, author={Chen, D and Lu, JC and Huo, XM and Yin, M}, year={2001}, month={Sep}, pages={275–292} }
 @article{lu_liu_yin_hughes-oliver_1999, title={Modeling restricted bivariate censored lowflow data}, volume={10}, ISSN={["1180-4009"]}, DOI={10.1002/(SICI)1099-095X(199903/04)10:2<125::AID-ENV340>3.3.CO;2-P}, abstractNote={Environmental studies often result in censored data. In this article, the lowflow quantiles Q*7,2 and Q*7,10 below a limit are treated as censored data. These streamflow quantiles are important for water resources planning and management. Our partial all-subsets censored regression procedure identifies a few important explanatory variables, such as drainage area, basin slope, soil-infiltration index, rainfall index, and some combinations of them. The proposed maximum likelihood estimation method incorporates the restriction Q*7,2≥Q*7,10 and the bivariate probability distribution of the quantiles to improve model quality. Analyses of the lowflow quantiles obtained from streams in West-Central Florida show that our procedure is more appropriate than the commonly used univariate main-effects models in predicting quantiles. Copyright © 1999 John Wiley & Sons, Ltd.}, number={2}, journal={ENVIRONMETRICS}, author={Lu, JC and Liu, SP and Yin, M and Hughes-Oliver, JM}, year={1999}, pages={125–136} }
 @article{li_lu_park_1999, title={Multivariate zero-inflated Poisson models and their applications}, volume={41}, ISSN={["0040-1706"]}, DOI={10.2307/1270992}, abstractNote={The zero-inflated Poisson (ZIP) distribution has been shown to be useful for modeling outcomes of manufacturing processes producing numerous defect-free products. When there are several types of defects, the multivariate ZIP (MZIP) model can be useful to detect specific process equipment problems and to reduce multiple types of defects simultaneously. This article proposes types of MZIP models and investigates distributional properties of an MZIP model. Finite-sample simulation studies show that, compared to the method of moments, the maximum likelihood method has smaller bias and variance, as well as more accurate coverage probability in estimating model parameters and zero-defect probability. Real-life examples from a major electronic equipment manufacturer illustrate how the proposed procedures are useful in a manufacturing environment for equipment-fault detection and for covariate effect studies.}, number={1}, journal={TECHNOMETRICS}, author={Li, CS and Lu, JC and Park, JH}, year={1999}, month={Feb}, pages={29–38} }
 @article{lu_holton_fenner_williams_kim_hartford_chen_roze_littlejohn_1998, title={A new device design methodology for manufacturability}, volume={45}, ISSN={0018-9383}, url={http://dx.doi.org/10.1109/16.661225}, DOI={10.1109/16.661225}, abstractNote={As future technology generations for integrated circuits continue to "shrink", TCAD tools must be made more central to manufacturing issues; thus, yield optimization and design for manufacturing (DFM) should be addressed integrally with performance and reliability when using TCAD during the initial product design. This paper defines the goals for DFM in TCAD simulations and outlines a formal procedure for achieving an optimized result (ODFM). New design of experiments (DOE), weighted least squares modeling and multiple-objective mean-variance optimization methods are developed as significant parts of the new ODFM procedure. Examples of designing a 0.18-/spl mu/m MOSFET device are given to show the impact of device design procedures on device performance distributions and sensitivity variance profiles.}, number={3}, journal={IEEE Transactions on Electron Devices}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Lu, J.-C. and Holton, W.C. and Fenner, J.S. and Williams, S.C. and Kim, K.W. and Hartford, A.H. and Chen, D. and Roze, K. and Littlejohn, M.A.}, year={1998}, month={Mar}, pages={634–642} }
 @article{hughes-oliver_lu_davis_gyurcsik_1998, title={Achieving uniformity in a semiconductor fabrication process using spatial modeling}, volume={93}, ISSN={["0162-1459"]}, DOI={10.2307/2669600}, abstractNote={Abstract Material is deposited onto the wafer surface during several steps of wafer fabrication. This material must be deposited evenly across the entire wafer surface, close to the targeted thickness, and with little wafer-to-wafer variability. But unequal variances across the wafer and under different process conditions, as well as nonstationary correlation across a wafer, make these goals difficult to achieve, because traditional methods for optimizing deposition processes assume homogeneity and independence. We avoid these assumptions and determine the best settings of process variables using physically motivated statistical models for the mean response, unequal variances, and nonstationary spatial correlation structure. Data from a rapid thermal chemical vapor deposition process is used to illustrate the approach. A simulation exercise demonstrates the advantages of fitting flexible variance models and using appropriate performance measures.}, number={441}, journal={JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION}, author={Hughes-Oliver, JM and Lu, JC and Davis, JC and Gyurcsik, RS}, year={1998}, month={Mar}, pages={36–45} }
 @article{chen_lu_hughes-oliver_li_1998, title={Asymptotic properties of maximum likelihood estimates for a bivariate exponential distribution and mixed censored data}, volume={48}, ISSN={["0026-1335"]}, DOI={10.1007/s001840050003}, number={2}, journal={METRIKA}, author={Chen, D and Lu, JC and Hughes-Oliver, JM and Li, CS}, year={1998}, pages={109–125} }
 @article{hughes-oliver_gonzalez-farias_lu_chen_1998, title={Parametric nonstationary correlation models}, volume={40}, ISSN={["0167-7152"]}, DOI={10.1016/S0167-7152(98)00103-5}, abstractNote={Stochastic processes observed over space often exhibit nonstationarity. Possible causes of nonstationarity include mean drift, heterogeneity of responses, or a correlation pattern that is not simply a function of the Euclidean distance between two spatial locations. This paper considers the latter. The need for nonstationary correlation models has been demonstrated in several application areas, including environmental monitoring of pollutants, and modeling of semiconductor fabrication processes. We present parametric nonstationary correlation models for capturing the effect of point sources. For example, if the response variable is carbon monoxide, then a smoke stack producing carbon monoxide would be considered a point source, and it is unreasonable to believe that correlation would not depend on proximity to the smoke stack. Our parametric models allow the consideration of multiple-point sources, as well as testing the strength of a particular source. These models have the usual anisotropic and isotropic exponential correlation functions as special cases.}, number={3}, journal={STATISTICS & PROBABILITY LETTERS}, author={Hughes-Oliver, JM and Gonzalez-Farias, G and Lu, JC and Chen, D}, year={1998}, month={Oct}, pages={267–278} }
 @article{liu_lu_kolpin_meeker_1997, title={Analysis of environmental data with censored observations}, volume={31}, ISSN={["0013-936X"]}, DOI={10.1021/es960695x}, abstractNote={The potential threats to humans and to terrestrial and aquatic ecosystems from environmental contamination could depend on the sum of the concentrations of different chemicals. However, direct summation of environmental data is not generally feasible because it is common for some chemical concentrations to be recorded as being below the analytical reporting limit. This creates special problems in the analysis of the data. A new model selection procedure, named forward censored regression, is introduced for selecting an appropriate model for environmental data with censored observations. The procedure is demonstrated using concentrations of atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine), deethylatrazine (DEA, 2-amino-4-chloro-6-isopropylamino-s-triazine), and deisopropylatrazine (DIA, 2-amino-4-chloro-6-ethylamino-s-triazine) in groundwater in the midwestern United States by using the data derived from a previous study conducted by the U.S. Geological Survey. More than 80% of the observations...}, number={12}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Liu, SP and Lu, JC and Kolpin, DW and Meeker, WQ}, year={1997}, month={Dec}, pages={3358–3362} }
 @article{brinkley_meyer_lu_1997, title={Functional marginality is important: response}, volume={46}, number={2}, journal={Applied Statistics [Journal of the Royal Statistical Society. Series C]}, author={Brinkley, P. A. and Meyer, K. P. and Lu, J.-C.}, year={1997}, pages={289–286} }
 @article{lu_park_yang_1997, title={Statistical inference of a time-to-failure distribution derived from linear degradation data}, volume={39}, ISSN={["0040-1706"]}, DOI={10.2307/1271503}, abstractNote={In the study of semiconductor degradation, records of transconductance loss or threshold voltage shift over time are useful in constructing the cumulative distribution function (cdf) of the time until the degradation reaches a specified level. In this article, we propose a model with random regression coefficients and a standard-deviation function for analyzing linear degradation data. Both analytical and empirical motivations of the model are provided. We estimate the model parameters, the cdf, and its quantiles by the maximum likelihood (ML) method and construct confidence intervals from the bootstrap, from the asymptotic normal approximation, and from inverting likelihood ratio tests. Simulations are conducted to examine the properties of the ML estimates and the confidence intervals. Analysis of an engineering dataset illustrates the proposed procedures.}, number={4}, journal={TECHNOMETRICS}, author={Lu, JC and Park, J and Yang, Q}, year={1997}, month={Nov}, pages={391–400} }