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ORCIDTechnometrics, Volume 63
Volume 63, Number 1, 2021
- Tamar Haizler, David M. Steinberg:
Factorial Designs for Online Experiments. 1-12 - Dario Azzimonti
, David Ginsbourger, Clément Chevalier, Julien Bect, Yann Richet:
Adaptive Design of Experiments for Conservative Estimation of Excursion Sets. 13-26 - Michael Grosskopf, Derek Bingham, Marvin L. Adams, W. Daryl Hawkins, Delia Perez-Nunez:
Generalized Computer Model Calibration for Radiation Transport Simulation. 27-39 - Boya Zhang, D. Austin Cole, Robert B. Gramacy:
Distance-Distributed Design for Gaussian Process Surrogates. 40-52 - Christopher Pope, John Paul Gosling, Stuart Barber, Jill S. Johnson, Takanobu Yamaguchi, Graham Feingold, Paul G. Blackwell:
Gaussian Process Modeling of Heterogeneity and Discontinuities Using Voronoi Tessellations. 53-63 - Kai Qu, Jonathan R. Bradley, Xufeng Niu:
Boundary Detection Using a Bayesian Hierarchical Model for Multiscale Spatial Data. 64-76 - Xiaochen Xian, Honghan Ye, Xin Wang, Kaibo Liu:
Spatiotemporal Modeling and Real-Time Prediction of Origin-Destination Traffic Demand. 77-89 - Brian P. Weaver, William Q. Meeker:
Bayesian Methods for Planning Accelerated Repeated Measures Degradation Tests. 90-99 - Sai Xiao, Athanasios Kottas, Bruno Sansó, Hyotae Kim:
Nonparametric Bayesian Modeling and Estimation for Renewal Processes. 100-115 - Thomas A. Metzger, Christopher T. Franck:
Detection of latent heteroscedasticity and group-based regression effects in linear models via Bayesian model selection. 116-126 - Necip Doganaksoy:
A Simplified Formulation of Likelihood Ratio Confidence Intervals Using a Novel Property. 127-135
- Feryaal Ahmed:
Data Management Using Stata: A Practical Handbook. 136-137 - Stan Lipovetsky:
Debunking Seven Terrorism Myths Using Statistics. 137-140 - Stan Lipovetsky:
The Equation of Knowledge: From Bayes' Rule to a Unified Philosophy of Science. 140-143 - Stan Lipovetsky:
Understanding Elections Through Statistics: Polling, Prediction, and Testing. 143-144 - Tony Pourmohamad:
Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences. 144-145
- S. Ejaz Ahmed:
Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, 2nd ed. 145
- Technometrics Editorial Collaborators. 146
Volume 63, Number 2, 2021
- Mostafa Reisi Gahrooei, Hao Yan, Kamran Paynabar, Jianjun Shi:
Multiple Tensor-on-Tensor Regression: An Approach for Modeling Processes With Heterogeneous Sources of Data. 147-159 - Sharmistha Guha, Rajarshi Guhaniyogi:
Bayesian Generalized Sparse Symmetric Tensor-on-Vector Regression. 160-170 - Shuyu Chu, Huijing Jiang, Zhengliang Xue, Xinwei Deng:
Adaptive Convex Clustering of Generalized Linear Models With Application in Purchase Likelihood Prediction. 171-183 - Jakob Raymaekers, Peter J. Rousseeuw:
Fast Robust Correlation for High-Dimensional Data. 184-198 - Gaurav Agarwal, Ying Sun:
Bivariate Functional Quantile Envelopes With Application to Radiosonde Wind Data. 199-211 - Jian-Feng Yang, Fasheng Sun, Hongquan Xu:
A Component-Position Model, Analysis and Design for Order-of-Addition Experiments. 212-224 - Shifeng Xiong:
The Reconstruction Approach: From Interpolation to Regression. 225-235 - Munir A. Winkel, Jonathan W. Stallrich, Curtis B. Storlie, Brian J. Reich:
Sequential Optimization in Locally Important Dimensions. 236-248 - Qian Wu, Xinwei Deng, Shiren Wang, Li Zeng:
Constrained Varying-Coefficient Model for Time-Course Experiments in Soft Tissue Fabrication. 249-262 - Yichao Wu:
Can't Ridge Regression Perform Variable Selection? 263-271
- Li-Pang Chen:
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. 272-273 - Stan Lipovetsky:
Advanced Statistics with Applications in R. 273-275 - Stan Lipovetsky:
Scientific Journeys: A Physicist Explores the Culture, History and Personalities of Science. 275-277 - Stan Lipovetsky:
R for Political Data Science: A Practical Guide. 277-278 - Stan Lipovetsky:
Understanding the Analytic Hierarchy Process. 278-279 - S. Ejaz Ahmed:
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modelling and Analysis of Big Data. 280
Volume 63, Number 3, 2021
- Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini:
Functional Regression Control Chart. 281-294 - Xueqi Zhao, Enrique del Castillo:
An Intrinsic Geometrical Approach for Statistical Process Control of Surface and Manifold Data. 295-312 - Kai Yang, Peihua Qiu:
Adaptive Process Monitoring Using Covariate Information. 313-328 - Jiuhai Chen, Lulu Kang, Guang Lin:
Gaussian Process Assisted Active Learning of Physical Laws. 329-342 - Xiaochen Zhu, Martin Slawski, P. Jonathon Phillips, Liansheng Larry Tang:
Order-Constrained ROC Regression With Application to Facial Recognition. 343-353 - Lu Lu, Bing Xing Wang, Yili Hong, Zhisheng Ye:
General Path Models for Degradation Data With Multiple Characteristics and Covariates. 354-369 - Chen Zhang, Hao Yan, Seungho Lee, Jianjun Shi:
Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning. 370-383 - Jialei Chen, Simon Mak, V. Roshan Joseph, Chuck Zhang:
Function-on-Function Kriging, With Applications to Three-Dimensional Printing of Aortic Tissues. 384-395 - Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King:
Robust Function-on-Function Regression. 396-409 - Jaesung Lee, Shiyu Zhou, Junhong Chen:
Statistical Modeling and Analysis of k-Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes. 410-420
- Stan Lipovetsky:
Book Reviews. 421-423 - Stan Lipovetsky:
Learning Microeconometrics with R. 424-425 - Stan Lipovetsky:
Linear Models with Python. 426-427 - Stan Lipovetsky:
Handbook of Item Response Theory, Volume 1, Models. 428-431 - Stan Lipovetsky:
Handbook of Item Response Theory, Statistical Tools, Volume 2, . 431-433 - Stan Lipovetsky:
Handbook of Item Response Theory: Applications (3). 433-437 - Wayne B. Nelson:
Statistical Methods for Reliability Data, Second Edition, . 437-440 - Abhirup Mallik:
Statistical Rethinking: A Bayesian Course with Examples in R and Stan. 440-441 - Srishti Vishwakarma, Vyacheslav Lyubchich:
Time Series Clustering and Classification. 441 - S. Ejaz Ahmed:
New Frontiers of Biostatistics and Bioinformatics. 441-442 - S. Ejaz Ahmed:
Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field. 442
Volume 63, Number 4, 2021
- Maria L. Weese, Jonathan W. Stallrich, Byran J. Smucker, David J. Edwards:
Strategies for Supersaturated Screening: Group Orthogonal and Constrained Var(s) Designs. 443-455 - Qin Wang, Xiangrong Yin:
Aggregate Inverse Mean Estimation for Sufficient Dimension Reduction. 456-465 - Trevor Harris, J. Derek Tucker, Bo Li, Lyndsay Shand:
Elastic Depths for Detecting Shape Anomalies in Functional Data. 466-476 - Xubo Yue, Raed Al Kontar:
Joint Models for Event Prediction From Time Series and Survival Data. 477-486 - W. Zachary Horton, Garritt L. Page, C. Shane Reese, Lindsey K. Lepley, McKenzie White:
Template Priors in Bayesian Curve Registration. 487-499 - Tzu-Hsiang Hung, Peter Chien:
A Random Fourier Feature Method for Emulating Computer Models With Gradient Information. 500-509 - Bledar A. Konomi, Georgios Karagiannis:
Bayesian Analysis of Multifidelity Computer Models With Local Features and Nonnested Experimental Designs: Application to the WRF Model. 510-522 - Kevin J. Wilson, Malcolm Farrow:
Assurance for Sample Size Determination in Reliability Demonstration Testing. 523-535 - Sutanoy Dasgupta, Debdeep Pati, Ian H. Jermyn, Anuj Srivastava:
Modality-Constrained Density Estimation via Deformable Templates. 536-547 - Ghulam A. Qadir, Ying Sun, Sebastian Kurtek:
Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment. 548-561
- Achieving Product Reliability: A Key to Business Success. 562-564
- Mathematical Statistics. 564-565
- Linear and Non-Linear System Theory. 565-566
- Advanced Engineering Mathematics. 566-570
- Subjective Well-Being and Social Media: Reconciling Big Data and Statistics. 570-572
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