Technometrics

Papers
(The TQCC of Technometrics is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
SPlit: An Optimal Method for Data Splitting78
Active Learning for Deep Gaussian Process Surrogates28
Transparent Sequential Learning for Statistical Process Control of Serially Correlated Data23
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control17
An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-Dimensional Streaming Data13
Assurance for Sample Size Determination in Reliability Demonstration Testing12
Super Resolution for Multi-Sources Image Stream Data Using Smooth and Sparse Tensor Completion and Its Applications in Data Acquisition of Additive Manufacturing11
The Temporal Overfitting Problem with Applications in Wind Power Curve Modeling10
A Multivariate Stochastic Degradation Model for Dependent Performance Characteristics10
Novelty and Primacy: A Long-Term Estimator for Online Experiments9
Strategies for Supersaturated Screening: Group Orthogonal and Constrained Var(s) Designs9
Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data9
Understanding the Analytic Hierarchy Process9
Anomaly Detection in Large-Scale Networks With Latent Space Models9
Deep Gaussian Process Emulation using Stochastic Imputation8
Joint Models for Event Prediction From Time Series and Survival Data8
Personalized Federated Learning via Domain Adaptation with an Application to Distributed 3D Printing8
Reliable Post-Signal Fault Diagnosis for Correlated High-Dimensional Data Streams8
Fast and Exact Leave-One-Out Analysis of Large-Margin Classifiers8
Image-Based Feedback Control Using Tensor Analysis7
PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models7
Label-Noise Robust Deep Generative Model for Semi-Supervised Learning7
Sequential Design of Multi-Fidelity Computer Experiments: Maximizing the Rate of Stepwise Uncertainty Reduction6
Prediction of Future Failures for Heterogeneous Reliability Field Data6
Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks6
Gaussian Process-Aided Function Comparison Using Noisy Scattered Data6
Class Maps for Visualizing Classification Results6
Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors5
Sequential Change-Point Detection for Mutually Exciting Point Processes5
Nonparametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns5
A Multifidelity Function-on-Function Model Applied to an Abdominal Aortic Aneurysm5
Selection of Two-Level Supersaturated Designs for Main Effects Models5
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python5
A Subsampling Method for Regression Problems Based on Minimum Energy Criterion5
Template Priors in Bayesian Curve Registration5
A Graphical Multi-Fidelity Gaussian Process Model, with Application to Emulation of Heavy-Ion Collisions5
An Information Geometry Approach to Robustness Analysis for the Uncertainty Quantification of Computer Codes5
Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments5
Statistical Modeling and Monitoring of Geometrical Deviations in Complex Shapes With Application to Additive Manufacturing5
A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling5
Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models5
A Gaussian Process Emulator Based Approach for Bayesian Calibration of a Functional Input4
Understanding Elections Through Statistics: Polling, Prediction, and Testing4
Functional PCA With Covariate-Dependent Mean and Covariance Structure4
Big Data and Social Science: Data Science Methods and Tools for Research and Practice4
Bayesian Analysis of Multifidelity Computer Models With Local Features and Nonnested Experimental Designs: Application to the WRF Model4
Model Mixing Using Bayesian Additive Regression Trees4
A General Modeling Framework for Network Autoregressive Processes4
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data4
Statistical Rethinking: A Bayesian Course with Examples in R and Stan4
Online Structural Change-Point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning4
Handbook of Item Response Theory, Volume 1, Models4
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling4
Probability, Choice, and Reason3
Constructing a Simulation Surrogate with Partially Observed Output3
Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences3
Toward Optimal Variance Reduction in Online Controlled Experiments3
A New Sparse-Learning Model for Maximum Gap Reduction of Composite Fuselage Assembly3
High-Dimensional Cost-constrained Regression Via Nonconvex Optimization3
A General Framework for Robust Monitoring of Multivariate Correlated Processes3
Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model3
Advanced Statistics with Applications in R3
Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data3
Statistical Methods for Reliability Data, Second Edition,3
Sequential Designs for Filling Output Spaces3
Multi-Output Calibration of a Honeycomb Seal via On-site Surrogates3
The Equation of Knowledge: From Bayes’ Rule to a Unified Philosophy of Science3
Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data3
Tensor-Based Temporal Control for Partially Observed High-Dimensional Streaming Data3
Functional Outlier Detection for Density-Valued Data with Application to Robustify Distribution-to-Distribution Regression3
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing3
Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation3
Efficient Model-Free Subsampling Method for Massive Data3
A Tweedie Compound Poisson Model in Reproducing Kernel Hilbert Space3
Detecting Changes in Covariance via Random Matrix Theory3
Math and Art: An Introduction to Visual Mathematics, 2nd ed.,3
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