Daniel W. Apley

发表

A cautious approach to robust design with model parameter uncertainty

Jeongbae Kim, Daniel W. Apley, D. Apley, 2011 .

A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality

Wei Chen, Daniel W. Apley, Miguel A. Bessa, 2017 .

An exploratory analysis approach for understanding variation in stochastic textured surfaces

Daniel W. Apley, Anh Tuan Bui, D. Apley, 2019, Comput. Stat. Data Anal..

Principal Components and Factor Analysis

Daniel W. Apley, 2003 .

Identifying and visualizing nonlinear variation patterns in multivariate manufacturing data

Daniel W. Apley, Feng Zhang, D. Apley, 2007 .

Reduction of Epistemic Model Uncertainty in Simulation-Based Multidisciplinary Design

Wei Chen, Zhen Jiang, Daniel W. Apley, 2016 .

Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Daniel W. Apley, Wei Chen, Paul D. Arendt, 2013 .

A nonstationary covariance based Kriging method for metamodeling in engineering design

Ying Xiong, Wei Chen, Daniel W. Apley, 2006 .

Guidelines for placing additional sensors to improve variation diagnosis in assembly processes

Daniel W. Apley, Yu Ding, 2007 .

Time Series Control Charts in the Presence of Model Uncertainty

Daniel W. Apley, 2002 .

A mode tracking method in modal metamodeling for structures with clustered eigenvalues

Jiong Tang, Zhenfei Zhan, Daniel W. Apley, 2020 .

Nominations Sought for 2018 William G. Hunter Award

Daniel W. Apley, 2018, Technometrics.

Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis

Daniel W. Apley, George Runger, Phillip Howard, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Performance and Robustness of Control Charting Methods for Autocorrelated Data

Daniel W. Apley, Chang-Ho Chin, D. Apley, 2008 .

Including a Nugget Effect in Lifted Brownian Covariance Models

Daniel W. Apley, Wenxin Jiang, Ning Zhang, 2020, SIAM/ASA J. Uncertain. Quantification.

Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation

Daniel W. Apley, Jeremy Staum, Yunpeng Sun, 2011, Oper. Res..

A Suboptimal N-Step-Ahead Cautious Controller for Adaptive Control Applications

Jianjun Shi, Daniel W. Apley, D. Apley, 1998 .

A better understanding of model updating strategies in validating engineering models

Ying Xiong, Wei Chen, Daniel W. Apley, 2009 .

Integrating Bayesian Calibration, Bias Correction, and Machine Learning for the 2014 Sandia Verification and Validation Challenge Problem

Wei Li, Wei Chen, Zhen Jiang, 2016 .

Preimages for variation patterns from kernel PCA and bagging

Daniel W. Apley, George Runger, Amit Shinde, 2014 .

자기상관 데이터의 통계적 공정관리를 위한 선형 필터 기법

Daniel W. Apley, 진창호, 2006 .

Patchwork Kriging for Large-scale Gaussian Process Regression pdf

Chiwoo Park, Daniel W. Apley, Chiwoo Park, 2017, J. Mach. Learn. Res..

Improved design of robust exponentially weighted moving average control charts for autocorrelated processes

Daniel W. Apley, Hyun Cheol Lee, D. Apley, 2011, Qual. Reliab. Eng. Int..

Cautious Control of Industrial Process Variability With Uncertain Input and Disturbance Model Parameters

Daniel W. Apley, Jeong-Bae Kim, D. Apley, 2004, Technometrics.

Scalable Adaptive Batch Sampling in Simulation-Based Design With Heteroscedastic Noise

Wei Chen, Siyu Tao, Daniel W. Apley, 2020, Journal of Mechanical Design.

Identifying Spatial Variation Patterns in Multivariate Manufacturing Processes

Daniel W. Apley, Ho-Young Lee, D. Apley, 2003, Technometrics.

A time-dependent proportional hazards survival model for credit risk analysis

Daniel W. Apley, X. Shan, Joon-Ku Im, 2012, J. Oper. Res. Soc..

A Monitoring and Diagnostic Approach for Stochastic Textured Surfaces

Daniel W. Apley, Anh Tuan Bui, 2018, Technometrics.

Batch Sample Design from Databases for Logistic Regression

Daniel W. Apley, Sanjay Mehrotra, Liwen Ouyang, 2017, Qual. Reliab. Eng. Int..

MLPCA Based Logistical Regression Analysis for Pattern Clustering in Manufacturing Processes

Feng Zhang, Daniel W. Apley, 2003, IDEAL.

Posterior Distribution Charts: A Bayesian Approach for Graphically Exploring a Process Mean

Daniel W. Apley, D. Apley, 2012, Technometrics.

Objective–Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Daniel W. Apley, Wei Chen, Paul D. Arendt, 2012, DAC 2012.

Towards a Better Understanding of the Role of Calibration and Bias Correction in Model Validation

Daniel W. Apley, Wei Chen, Paul D. Arendt, 2010 .

Diagnostics in Disassembly Unscrewing Operations

Daniel W. Apley, Jianjun Shi, G. Seliger, 1998 .

Lifted Brownian Kriging Models

Daniel W. Apley, Matthew Plumlee, M. Plumlee, 2017, Technometrics.

Singularity Issue in Dimensional Variation Diagnosis of Multi-Station Assembly Processes

Yu Ding, Daniel W. Apley, Abhishek Gupta, 2003 .

Nonhierarchical multi‐model fusion using spatial random processes

Wei Chen, Daniel W. Apley, Zhen Jiang, 2016 .

Monitoring for changes in the nature of stochastic textured surfaces

Daniel W. Apley, Anh Tuan Bui, D. Apley, 2018, Journal of Quality Technology.

Designed sampling from large databases for controlled trials

Daniel W. Apley, Sanjay Mehrotra, Liwen Ouyang, 2015 .

Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors pdf

Daniel W. Apley, Kungang Zhang, Anh T. Bui, 2020, ArXiv.

Understanding the Effects of Model Uncertainty in Robust Design With Computer Experiments

Daniel W. Apley, Wei Chen, Jun Liu, 2006 .

Resource Allocation for Reduction of Epistemic Uncertainty in Simulation-Based Multidisciplinary Design

Wei Chen, Daniel W. Apley, Zhen Jiang, 2015, DAC 2015.

Robust design of residual-based EWMA control charts

Daniel W. Apley, Hyun Cheol Lee, 2004 .

Tolerance allocation for compliant beam structure assemblies

Daniel W. Apley, Jianjun Shi, B. W. Shiu, 2003 .

Adaptive cautious predictive controller for real-time implementation

Jianjun Shi, Daniel W. Apley, 1994 .

Identifying and visualizing part-to-part variation with spatially dense optical dimensional metrology data

Daniel W. Apley, George C. Runger, Zhenyu Shi, 2019 .

Multi-response approach to improving identifiability in model calibration

Wei Chen, Zhen Jiang, Daniel W. Apley, 2016 .

The GLRT for statistical process control of autocorrelated processes

Jianjun Shi, Daniel W. Apley, D. Apley, 1999 .

Optimal Design of Second-Order Linear Filters for Control Charting

Daniel W. Apley, Chang-Ho Chin, D. Apley, 2006, Technometrics.

A fault detection, isolation, and identification technique for complex MISO linear systems

Daniel W. Apley, Jainjun Shi, D. Apley, 1994, Proceedings of 1994 American Control Conference - ACC '94.

Fully-sequential space-filling design algorithms for computer experiments

Daniel W. Apley, Boyang Shang, D. Apley, 2020, Journal of Quality Technology.

Enhanced Collaborative Optimization Using Alternating Direction Method of Multipliers

Guang Yang, Siyu Tao, Wei Chen, 2018 .

Uncertainty propagation of frequency response functions using a multi-output Gaussian Process model

Wei Chen, Zhenfei Zhan, Daniel W. Apley, 2019, Computers & Structures.

Input Mapping for Model Calibration with Application to Wing Aerodynamics

Wei Chen, Siyu Tao, Daniel W. Apley, 2019, AIAA Journal.

Local Gaussian Process Approximation for Large Computer Experiments

Daniel W. Apley, Robert B. Gramacy, R. Gramacy, 2013, 1303.0383.

Image denoising with a multi-phase kernel principal component approach and an ensemble version

Daniel W. Apley, George C. Runger, Anshuman Sahu, 2011, 2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).

Scalable Objective-Driven Batch Sampling in Simulation-Based Design for Models With Heteroscedastic Noise

Wei Chen, Siyu Tao, Daniel W. Apley, 2020, Volume 11B: 46th Design Automation Conference (DAC).

Projection-free kernel principal component analysis for denoising

Daniel W. Apley, George C. Runger, Anh Tuan Bui, 2019, Neurocomputing.

Bayesian Optimization for Simulation-Based Design of Multi-Model Systems

Wei Chen, Siyu Tao, Daniel W. Apley, 2020, DAC 2020.

A Statistical Process Control Method for Autocorrelated Data Using a GLRT

Jianjun Shi, Daniel W. Apley, 1994 .

Feature selection for noisy variation patterns using kernel principal component analysis

Daniel W. Apley, George C. Runger, Anshuman Sahu, 2014, Knowl. Based Syst..

A Spatial-Random-Process Based Multidisciplinary System Uncertainty Propagation Approach With Model Uncertainty

Wei Chen, Zhen Jiang, Daniel W. Apley, 2015 .

Optimal design of general linear filters for statistical process control

Daniel W. Apley, Chang-Ho Chin, 2004 .

"Identifying and Visualizing Root Causes of Manufacturing Variation with In-Process Measurement Data

Daniel W. Apley, 2005 .

Design of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes With Model Uncertainty

Daniel W. Apley, Hyun Cheol Lee, 2003, Technometrics.

Tangent Hyperplane Kernel Principal Component Analysis for Denoising

Daniel W. Apley, George C. Runger, Joon-Ku Im, 2012, IEEE Transactions on Neural Networks and Learning Systems.

The 2017 Technometrics Prizes

Daniel W. Apley, 2019, Technometrics.

Visualizing the effects of predictor variables in black box supervised learning models

Daniel W. Apley, D. Apley, Jingyu Zhu, 2016, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Technometrics Editorial Collaborators

Daniel W. Apley, 2018, Technometrics.

Daniel W. Apley, Fugee Tsung, Lianjie Shu, 2002 .

Leveraging the nugget parameter for efficient Gaussian process modeling

Wei Chen, Siyu Tao, Daniel W. Apley, 2018 .

Blind Identification of Manufacturing Variation Patterns by Combining Source Separation Criteria

Daniel W. Apley, Xuemei Shan, D. Apley, 2008, Technometrics.

Diagnosis of Multiple Fixture Faults in Panel Assembly

Daniel W. Apley, Jianjun Shi, D. Apley, 1996 .

A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records

Daniel W. Apley, Sanjay Mehrotra, Liwen Ouyang, 2016, J. Am. Medical Informatics Assoc..

SPC for Low Volume Composite Manufacturing at BHTI

Daniel W. Apley, 2000 .

Technometrics 2017 Editor's Report

Daniel W. Apley, 2017, Technometrics.

Integration of Normative Decision-Making and Batch Sampling for Global Metamodeling

Wei Chen, Daniel W. Apley, Matthew Plumlee, 2020 .

Identifying Variation Patterns in Manufacturing Measurement Data

Daniel W. Apley, 2008 .

Discovering the Nature of Variation in Nonlinear Profile Data

Daniel W. Apley, George C. Runger, Zhenyu Shi, 2016, Technometrics.

A System Uncertainty Propagation Approach With Model Uncertainty Quantification in Multidisciplinary Design

Wei Chen, Daniel W. Apley, Wei Li, 2014, DAC 2014.

Multiple Responses and Design of Experiments for Improving Identifiability in Model Calibration

Daniel W. Apley, Paul D. Arendt, Wei Chen, 2011 .

Identifying nonlinear variation patterns with deep autoencoders

Daniel W. Apley, George C. Runger, Phillip Howard, 2018, IISE Transactions.

A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors

Wei Chen, Siyu Tao, Daniel W. Apley, 2018, Technometrics.

A characterization of diagnosability conditions for variance components analysis in assembly operations

Yu Ding, Daniel W. Apley, Yu Ding, 2005, IEEE Transactions on Automation Science and Engineering.

Improving Identifiability in Model Calibration Using Multiple Responses

Daniel W. Apley, Wei Chen, Paul D. Arendt, 2012, DAC 2011.

The dynamic T 2 chart for monitoring feedback-controlled processes

Daniel W. Apley, Fugee Tsung, 2002 .

An order downdating algorithm for tracking system order and parameters in recursive least squares identification

Daniel W. Apley, Jianjun Shi, 1999, IEEE Trans. Signal Process..

An Optimal Filter Design Approach to Statistical Process Control

Daniel W. Apley, Chang-Ho Chin, 2007 .

Understanding the effects of model uncertainty in robust design with computer experiments

Daniel W. Apley, Wei Chen, Jun Liu, 2006, DAC 2006.

Singularity Issues in Fixture Fault Diagnosis for Multi-Station Assembly Processes

Daniel W. Apley, Yu Ding, Abhishek Gupta, 2004 .

Updating Predictive Models: Calibration, Bias Correction and Identifiability

Daniel W. Apley, Wei Chen, Paul D. Arendt, 2010, DAC 2010.

A Factor-Analysis Method for Diagnosing Variability in Mulitvariate Manufacturing Processes

Daniel W. Apley, Jianjun Shi, D. Apley, 2001, Technometrics.

Diagnosing Manufacturing Variation Using Second-Order and Fourth-Order Statistics

Daniel W. Apley, Ho Young Lee, 2004 .

Multi-Model Bayesian Optimization for Simulation-Based Design

Daniel W. Apley, Wei Chen, Siyu Tao, 2021 .

Bias-corrected Estimation of the Density of a Conditional Expectation in Nested Simulation Problems

Daniel W. Apley, Jeremy Staum, Ran Yang, 2021, ACM Trans. Model. Comput. Simul..

Data-Driven Design via Scalable Gaussian Processes for Multi-Response Big Data With Qualitative Factors

Daniel W. Apley, Akshay Iyer, Suraj Yerramilli, 2021, Volume 3A: 47th Design Automation Conference (DAC).

Coefficient tree regression for generalized linear models

Daniel W. Apley, Edward C. Malthouse, Özge Sürer, 2021, Statistical analysis and data mining.

Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data

Daniel W. Apley, Anh Tuan Bui, D. Apley, 2021, Technometrics.

Improving Identifiability in Model Calibration Using Multiple Responses

David Gorsich, Daniel W. Apley, David Lamb, 2012 .

Simultaneous Identification of Premodeled and Unmodeled Variation Patterns*

Daniel W. Apley, D. Apley, Ho Young Lee, 2010 .

The dynamic T2 chart for monitoring feedback-controlled processes

Daniel W. Apley, Fugee Tsung, 2002 .

A cautious minimum variance controller with ARIMA disturbances

Daniel W. Apley, D. Apley, 2004 .

Fractional Brownian Fields for Response Surface Metamodeling

Daniel W. Apley, Ning Zhang, D. Apley, 2014 .

Journal of Quality Technology: Message from the editor

Daniel W. Apley, D. Apley, 2010 .

A Cautious Approach to Robust Design with Model Uncertainty

Daniel W. Apley, D. Apley, Jeongbae Kim, 2002 .

Adaptive CUSUM procedures with EWMA-based shift estimators

Wei Jiang, Daniel W. Apley, Lianjie Shu, 2008 .

spc4sts: Statistical process control for stochastic textured surfaces in R

Daniel W. Apley, Anh Tuan Bui, D. Apley, 2020, Journal of Quality Technology.

Preposterior Analysis to Select Experimental Responses for Improving Identifiability in Model Uncertainty Quantification

Wei Chen, Daniel W. Apley, Zhen Jiang, 2013, DAC 2013.

Brownian Integrated Covariance Functions for Gaussian Process Modeling: Sigmoidal Versus Localized Basis Functions

Daniel W. Apley, Ning Zhang, D. Apley, 2016 .

Estimating the density of a conditional expectation

Daniel W. Apley, Shane G. Henderson, David Ruppert, 2016 .

Robustness Comparison of Exponentially Weighted Moving-Average Charts on Autocorrelated Data and on Residuals

Daniel W. Apley, D. Apley, Hyun Cheol Lee, 2008 .