OOIR: Observatory of International Research

Papers

(The median citation count of Technometrics is 1. 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.)

Article	Citations
SPlit: An Optimal Method for Data Splitting	78
Active Learning for Deep Gaussian Process Surrogates	28
Transparent Sequential Learning for Statistical Process Control of Serially Correlated Data	23
Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control	17
An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-Dimensional Streaming Data	13
Assurance for Sample Size Determination in Reliability Demonstration Testing	12
Super Resolution for Multi-Sources Image Stream Data Using Smooth and Sparse Tensor Completion and Its Applications in Data Acquisition of Additive Manufacturing	11
The Temporal Overfitting Problem with Applications in Wind Power Curve Modeling	10
A Multivariate Stochastic Degradation Model for Dependent Performance Characteristics	10
Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data	9
Understanding the Analytic Hierarchy Process	9
Anomaly Detection in Large-Scale Networks With Latent Space Models	9
Novelty and Primacy: A Long-Term Estimator for Online Experiments	9
Strategies for Supersaturated Screening: Group Orthogonal and Constrained Var(s) Designs	9
Deep Gaussian Process Emulation using Stochastic Imputation	8
Joint Models for Event Prediction From Time Series and Survival Data	8
Personalized Federated Learning via Domain Adaptation with an Application to Distributed 3D Printing	8
Reliable Post-Signal Fault Diagnosis for Correlated High-Dimensional Data Streams	8
Fast and Exact Leave-One-Out Analysis of Large-Margin Classifiers	8
Image-Based Feedback Control Using Tensor Analysis	7
PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models	7
Label-Noise Robust Deep Generative Model for Semi-Supervised Learning	7
Sequential Design of Multi-Fidelity Computer Experiments: Maximizing the Rate of Stepwise Uncertainty Reduction	6
Prediction of Future Failures for Heterogeneous Reliability Field Data	6
Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks	6

Gaussian Process-Aided Function Comparison Using Noisy Scattered Data	6
Class Maps for Visualizing Classification Results	6
Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors	5
Sequential Change-Point Detection for Mutually Exciting Point Processes	5
Nonparametric Control Charts for Monitoring Serial Dependence based on Ordinal Patterns	5
A Multifidelity Function-on-Function Model Applied to an Abdominal Aortic Aneurysm	5
Selection of Two-Level Supersaturated Designs for Main Effects Models	5
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python	5
A Subsampling Method for Regression Problems Based on Minimum Energy Criterion	5
Template Priors in Bayesian Curve Registration	5
A Graphical Multi-Fidelity Gaussian Process Model, with Application to Emulation of Heavy-Ion Collisions	5
An Information Geometry Approach to Robustness Analysis for the Uncertainty Quantification of Computer Codes	5
Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments	5
Statistical Modeling and Monitoring of Geometrical Deviations in Complex Shapes With Application to Additive Manufacturing	5
A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling	5
Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models	5
Functional PCA With Covariate-Dependent Mean and Covariance Structure	4
Big Data and Social Science: Data Science Methods and Tools for Research and Practice	4
Bayesian Analysis of Multifidelity Computer Models With Local Features and Nonnested Experimental Designs: Application to the WRF Model	4
Model Mixing Using Bayesian Additive Regression Trees	4
A General Modeling Framework for Network Autoregressive Processes	4
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data	4
Statistical Rethinking: A Bayesian Course with Examples in R and Stan	4
Online Structural Change-Point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning	4
Handbook of Item Response Theory, Volume 1, Models	4
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling	4
A Gaussian Process Emulator Based Approach for Bayesian Calibration of a Functional Input	4
Understanding Elections Through Statistics: Polling, Prediction, and Testing	4
Constructing a Simulation Surrogate with Partially Observed Output	3
Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences	3
Toward Optimal Variance Reduction in Online Controlled Experiments	3
A New Sparse-Learning Model for Maximum Gap Reduction of Composite Fuselage Assembly	3
High-Dimensional Cost-constrained Regression Via Nonconvex Optimization	3
A General Framework for Robust Monitoring of Multivariate Correlated Processes	3
Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model	3
Advanced Statistics with Applications in R	3
Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data	3
Statistical Methods for Reliability Data, Second Edition,	3
Sequential Designs for Filling Output Spaces	3
Multi-Output Calibration of a Honeycomb Seal via On-site Surrogates	3
The Equation of Knowledge: From Bayes’ Rule to a Unified Philosophy of Science	3
Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data	3
Tensor-Based Temporal Control for Partially Observed High-Dimensional Streaming Data	3
Functional Outlier Detection for Density-Valued Data with Application to Robustify Distribution-to-Distribution Regression	3
Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing	3
Adaptive Sampling for Monitoring Multi-Profile Data with Within-and-between Profile Correlation	3
Efficient Model-Free Subsampling Method for Massive Data	3
A Tweedie Compound Poisson Model in Reproducing Kernel Hilbert Space	3
Detecting Changes in Covariance via Random Matrix Theory	3
Math and Art: An Introduction to Visual Mathematics, 2nd ed.,	3

Probability, Choice, and Reason	3
Robust Multivariate Functional Control Chart	2
JST-RR Model: Joint Modeling of Ratings and Reviews in Sentiment-Topic Prediction	2
Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment	2
A Sharper Computational Tool for Regression	2
Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments	2
D- andA-Optimal Screening Designs	2
Statistical Modeling of the Effectiveness of Preventive Maintenance for Repairable Systems	2
On Censoring Time in Statistical Monitoring of Lifetime Data	2
A Class of Hierarchical Multivariate Wiener Processes for Modeling Dependent Degradation Data	2
Linear Models with Python	2
Locally Optimal Design for A/B Tests in the Presence of Covariates and Network Dependence	2
Manhattan Project: The Story of the Century, by Bruce Cameron Reed. Springer Nature Switzerland AG, 2020,	2
Statistical Process Monitoring of Artificial Neural Networks	2
A Scalable Gaussian Process for Large-Scale Periodic Data	2
Adaptive Partially Observed Sequential Change Detection and Isolation	2
Editorial: Special Issue on Industry 4.0	2
Spatial Rank-Based Augmentation for Nonparametric Online Monitoring and Adaptive Sampling of Big Data Streams	2
Kernel-based Sensitivity Analysis for (Excursion) Sets	2
Calibration of Imperfect Geophysical Models by Multiple Satellite Interferograms with Measurement Bias	2
Feature Detection and Hypothesis Testing for Extremely Noisy Nanoparticle Images using Topological Data Analysis	2
Spectral Clustering on Spherical Coordinates Under the Degree-Corrected Stochastic Blockmodel	2
Active Learning for a Recursive Non-Additive Emulator for Multi-Fidelity Computer Experiments	2
Handbook of Measurement Error Models	2
Towards Improved Heliosphere Sky Map Estimation with Theseus	1
Modality-Constrained Density Estimation via Deformable Templates	1
Mesh-Clustered Gaussian Process Emulator for Partial Differential Equation Boundary Value Problems	1
Advanced Engineering Mathematics	1
Spatio-Temporal Analysis and Prediction of Mass Telecommunication Base Station Failure Events	1
A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets	1
Analyzing Spatial Models of Choice and Judgment, Second Edition	1
Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences	1
Inference for the Optimum Using Linear Regression Models with Discrete Inputs	1
R for Political Data Science: A Practical Guide	1
Geometry in Our Three-Dimensional World	1
Sensitivity Prewarping for Local Surrogate Modeling	1
Transfer Learning with Large-Scale Quantile Regression	1
Temporal Characterization and Filtering of Sensor Data to Support Anomaly Detection	1
Minimum Regularized Covariance Trace Estimator and Outlier Detection for Functional Data	1
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, 2nd ed. Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, 2nd ed . Wayne L.	1
Inverse Models for Estimating the Initial Condition of Spatio-Temporal Advection-Diffusion Processes	1
Robust Low-Rank Tensor Decomposition with the L ₂ Criterion	1
Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data	1
Federated Multiple Tensor-on-Tensor Regression (FedMTOT) for Multimodal Data Under Data-Sharing Constraints	1
Chance, Logic and Intuition: An Introduction to the Counter-Intuitive Logic of Chance	1
Moving Sum Procedure for Change Point Detection under Piecewise Linearity	1
Federated Multi-Output Gaussian Processes	1
Explanatory Model Analysis: Explore, Explain and Examine Predictive Models,	1
A Covariate-Regulated Sparse Subspace Learning Model and Its Application to Process Monitoring and Fault Isolation	1
Foundations of Statistics for Data Scientists: With R and Python	1
Measurement Models for Psychological Attributes	1
Editorial Announcement, V. Roshan Joseph, Editor	1
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modelling and Analysis of Big Data	1
All the Math You’ll Ever Need: A Self-Teaching Guide (3rd Edition) All the Math You’ll Ever Need: A Self-Teaching Guide ( 3rd Edition )	1
PERCEPT: A New Online Change-Point Detection Method using Topological Data Analysis	1
Handbook of Regression Modeling in People Analytics: With Examples in R and Python,	1
Drift versus Shift: Decoupling Trends and Changepoint Analysis	1
Mathematical Modeling: Models, Analysis and Applications, 2nd Edition Mathematical Modeling: Models, Analysis and Applications, 2nd Edition , by Sandip Banerjee, Boka Ra	1
Gaussian Process Emulation for High-Dimensional Coupled Systems	1
Statistical Process Monitoring from Industry 2.0 to Industry 4.0: Insights into Research and Practice	1
A Random Fourier Feature Method for Emulating Computer Models With Gradient Information	1
Discrepancy Measures for Global Sensitivity Analysis	1
Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments	1
Statistical Universals of Language: Mathematical Chance vs. Human Choice	1
Bayesian Modeling and Inference for One-Shot Experiments	1
Using BART to Perform Pareto Optimization and Quantify its Uncertainties	1
Data-Driven Determination of the Number of Jumps in Regression Curves	1
Robust and Efficient Parametric Spectral Density Estimation for High-Throughput Data	1
The Effect: An Introduction to Research Design and Causality	1
Book Review	1