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Selection and Aggregation of Conformal Prediction Sets J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-17 Yachong Yang, Arun Kumar Kuchibhotla
Conformal prediction is a generic methodology for finite-sample valid distribution-free prediction. This technique has garnered a lot of attention in the literature partly because it can be applied...
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Statistical Methods in Health Disparity Research. J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-17 Susan M. Paddock
Published in Journal of the American Statistical Association (Just accepted, 2024)
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Deep Learning and Scientific Computing with R torch Am. Stat. (IF 1.8) Pub Date : 2024-04-17 Yang Ni
Published in The American Statistician (Vol. 78, No. 2, 2024)
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An Introduction to R and Python for Data Analysis: A Side-by-Side Approach. Am. Stat. (IF 1.8) Pub Date : 2024-04-17 Gabriel Wallin
Published in The American Statistician (Vol. 78, No. 2, 2024)
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On Point Estimators for Gamma and Beta Distributions Am. Stat. (IF 1.8) Pub Date : 2024-04-17 Nickos D. Papadatos
Let X1,…,Xn be a random sample from the gamma distribution with density f(x)=λαxα−1e−λx/Γ(α), x > 0, where both α>0 (the shape parameter) and λ>0 (the reciprocal scale parameter) are unknown. The m...
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Introduction to Environmental Data Science J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-16 Timothée Poisot
Published in Journal of the American Statistical Association (Just accepted, 2024)
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Introduction to Statistical Modelling and Inference Am. Stat. (IF 1.8) Pub Date : 2024-04-17 Nianpin Cheng, Beth Chance
Published in The American Statistician (Ahead of Print, 2024)
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Statistical Theory: A Concise Introduction, 2nd ed. Am. Stat. (IF 1.8) Pub Date : 2024-04-17 Juan Sosa
Published in The American Statistician (Ahead of Print, 2024)
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Review of Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in R (2nd ed.) Struct. Equ. Model. (IF 6.0) Pub Date : 2024-04-16 Virginia Rosa da Silva
Published in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Dissecting gene expression heterogeneity: generalized Pearson correlation squares and the K-lines clustering algorithm J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-15 Jingyi Jessica Li, Heather J. Zhou, Peter J. Bickel, Xin Tong
Motivated by the pressing needs for dissecting heterogeneous relationships in gene expression data, here we generalize the squared Pearson correlation to capture a mixture of linear dependences bet...
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Sharp-SSL: Selective high-dimensional axis-aligned random projections for semi-supervised learning J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-12 Tengyao Wang, Edgar Dobriban, Milana Gataric, Richard J. Samworth
We propose a new method for high-dimensional semi-supervised learning problems based on the careful aggregation of the results of a low-dimensional procedure applied to many axis-aligned random pro...
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Problem-based scenario generation by decomposing output distributions Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-12 Benjamin S. Narum, Jamie Fairbrother, Stein W. Wallace
Scenario generation is required for most applications of stochastic programming to evaluate the expected effect of decisions made under uncertainty. We propose a novel and effective problem-based scenario generation method for two-stage stochastic programming that is agnostic to the specific stochastic program and kind of distribution. Our contribution lies in studying how an output distribution may
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Coexchangeable process modelling for uncertainty quantification in joint climate reconstruction J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-11 Lachlan Astfalck, Daniel Williamson, Niall Gandy, Lauren Gregoire, Ruza Ivanovic
Any experiment with climate models relies on a potentially large set of spatio-temporal boundary conditions. These can represent both the initial state of the system and/or forcings driving the mod...
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Handling Measurement Error and Omitted Confounders Considering Informativeness of the Confounding Effect under Mediation Modeling Struct. Equ. Model. (IF 6.0) Pub Date : 2024-04-10 Qian Zhang, Qi Wang
In the article, we focused on the issues of measurement error and omitted confounders while conducting mediation analysis under experimental studies. Depending on informativeness of the confounders...
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An exact method for a last-mile delivery routing problem with multiple deliverymen Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-10 Fernando Senna, Leandro C. Coelho, Reinaldo Morabito, Pedro Munari
The demand for efficient last-mile delivery systems in large cities creates an opportunity to develop innovative logistics schemes. In this paper, we study a problem in which each vehicle may travel with more than one deliveryman to serve multiple customers with a single stop of the vehicle, increasing the delivery efficiency. We extend the vehicle routing problem with time windows and multiple deliverymen
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Sobolev Calibration of Imperfect Computer Models J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-09 Qingwen Zhang, Wenjia Wang
Calibration refers to the statistical estimation of unknown model parameters in computer experiments, such that computer experiments can match underlying physical systems. This work develops a new ...
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Efficient Nonparametric Estimation of Stochastic Policy Effects with Clustered Interference J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-09 Chanhwa Lee, Donglin Zeng, Michael G. Hudgens
Interference occurs when a unit’s treatment (or exposure) affects another unit’s outcome. In some settings, units may be grouped into clusters such that it is reasonable to assume that interference...
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50 years of metaheuristics Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-09 Rafael Martí, Marc Sevaux, Kenneth Sörensen
In this paper, we review the milestones in the development of heuristic methods for optimization over the last 50 years. We propose a critical analysis of the main findings and contributions, mainly from a European perspective. Starting with the roots of the area that can be traced back to the classical philosophers, we follow the historical path of heuristics and metaheuristics in the field of operations
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Partnering with Authors to Enhance Reproducibility at JASA J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-08 Julia Wrobel, Emily C. Hector, Lorin Crawford, Lucy D’Agostino McGowan, Natalia da Silva, Jeff Goldsmith, Stephanie Hicks, Michael Kane, Youjin Lee, Vinicius Mayrink, Christopher J. Paciorek, Therri Usher, Julian Wolfson
Published in Journal of the American Statistical Association (Just accepted, 2024)
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Multilevel Factor Mixture Modeling: A Tutorial for Multilevel Constructs Struct. Equ. Model. (IF 6.0) Pub Date : 2024-04-05 Chunhua Cao, Yan Wang, Eunsook Kim
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterog...
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A generic approach to conference scheduling with integer programming Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-06 Yaroslav Pylyavskyy, Peter Jacko, Ahmed Kheiri
Conferences are a key aspect of communicating knowledge, and their schedule plays a vital role in meeting the expectations of participants. Given that many conferences have different constraints and objectives, different mathematical models and heuristic methods have been designed to address rather specific requirements of the conferences being studied per se. We present a penalty system that allows
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Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacy J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-05 Antonio R. Linero
Bayesian additive regression trees have seen increased interest in recent years due to their ability to combine machine learning techniques with principled uncertainty quantification. The Bayesian ...
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Inferring independent sets of Gaussian variables after thresholding correlations J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-05 Arkajyoti Saha, Daniela Witten, Jacob Bien
We consider testing whether a set of Gaussian variables, selected from the data, is independent of the remaining variables. This set is selected via a very simple approach: these are the variables ...
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Boldness-Recalibration for Binary Event Predictions Am. Stat. (IF 1.8) Pub Date : 2024-04-04 Adeline P. Guthrie, Christopher T. Franck
Probability predictions are essential to inform decision making across many fields. Ideally, probability predictions are (i) well calibrated, (ii) accurate, and (iii) bold, i.e., spread out enough ...
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Accelerated Double-Sketching Subspace Newton Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-03 Jun Shang, Haishan Ye, Xiangyu Chang
This paper proposes a second-order stochastic algorithm called Accelerated Double-Sketching Subspace Newton (ADSSN) to solve large-scale optimization problems with high dimensional feature spaces and substantial sample sizes. The proposed ADSSN has two computational superiority. First, ADSSN achieves a fast local convergence rate by exploiting Nesterov’s acceleration technique. Second, by taking full
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Robust decisions for heterogeneous agents via certainty equivalents Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-04-03 Anne G. Balter, Nikolaus Schweizer
We study the problem of a planner who resolves risk–return trade-offs – like financial investment decisions – on behalf of a collective of agents with heterogeneous risk preferences. The planner’s objective is a two-stage utility functional where an outer utility function is applied to the distribution of the agents’ certainty equivalents from a given decision. Assuming lognormal risks and heterogeneous
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Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-04-01 Jacob Dorn, Kevin Guo, Nathan Kallus
We consider the problem of constructing bounds on the average treatment effect (ATE) when unmeasured confounders exist but have bounded influence. Specifically, we assume that omitted confounders c...
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To Be Long or To Be Wide: How Data Format Influences Convergence and Estimation Accuracy in Multilevel Structural Equation Modeling Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-27 Julia-Kim Walther, Martin Hecht, Benjamin Nagengast, Steffen Zitzmann
A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect the...
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Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information* J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-27 Shujie Ma, Po-Yao Niu, Yichong Zhang, Yinchu Zhu
This paper investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available. The model consists of two parts. One part is a low-rank...
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Automatic regenerative simulation via non-reversible simulated tempering J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-27 Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Côté
Simulated Tempering (ST) is an MCMC algorithm for complex target distributions that operates on a path between the target and a more amenable reference distribution. Crucially, if the reference ena...
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CARE: Large Precision Matrix Estimation for Compositional Data J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-27 Shucong Zhang, Huiyuan Wang, Wei Lin
High-dimensional compositional data are prevalent in many applications. The simplex constraint poses intrinsic challenges to inferring the conditional dependence relationships among the components ...
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Using SymPy (Symbolic Python) for Understanding Structural Equation Modeling Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-27 Joel S. Steele, Kevin J. Grimm
Structural Equation Modeling (SEM) continues to grow in popularity with numerous articles, books, courses, and workshops available to help researchers become proficient with SEM quickly. However, f...
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Overall Model Fit Does Not Imply Linearity in Longitudinal Structural Equation Models: Examining Linear Change Over Time Using Latent Variable Modeling Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-27 Tenko Raykov, Christine DiStefano, Natalja Menold
This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemen...
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Home chemotherapy delivery: An integrated production scheduling and multi-trip vehicle routing problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-28 Yasemin Arda, Diego Cattaruzza, Véronique François, Maxime Ogier
Home chemotherapy systems allow the administration of cancer treatments at a patient’s residence, avoiding an admission to inpatient care facilities. This innovative health care model is interesting both economically and on a human level. It also raises several logistical challenges. This paper focuses on one of the optimization problems arising in the context of home chemotherapy services, where a
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2024 Editors’ awards for excellence in reviewing Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-28 Roman Słowiński Co-ordinating Editor
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Configuring systems to be viable in a crisis: The role of intuitive decision-making Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-28 Ayham Fattoum, Simos Chari, Duncan Shaw
Decision-making in complex systems becomes even more challenging when the environment creates volatile, uncertain, complex, and ambiguous conditions that disrupt operations. In these settings, the viable system model (VSM) advocates that delegated autonomy, appropriately calibrated, can help decision-makers deal with disruptions quickly to preserve system viability and performance. However, the delegated
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Working along both lines? The relationship between government green publicity and emissions tax Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-27 Liqun Wei, Libin Zhang, Wanying Wei, Xiaohong Chen, Kai Wang
Emissions reduction has long been the most concerning environmental issue. To promote emissions reduction among firms, governments have adopted mandatory tools such as emissions tax and voluntary guidance such as government green publicity. This paper investigates the interaction between emissions tax and government green publicity and analyzes the optimal decisions when the government combines these
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Tractable Bayesian inference for an unidentified simple linear regression model Am. Stat. (IF 1.8) Pub Date : 2024-03-26 Robert Calvert Jump
In this paper, I propose a tractable approach to Bayesian inference in a simple linear regression model for which the standard exogeneity assumption does not hold. By specifying a beta prior for th...
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Mathematical programming for simultaneous feature selection and outlier detection under l1 norm Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-26 Michele Barbato, Alberto Ceselli
The goal of simultaneous feature selection and outlier detection is to determine a sparse linear regression vector by fitting a dataset possibly affected by the presence of outliers.
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Biased random-key genetic algorithms: A review Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-26 Mariana A. Londe, Luciana S. Pessoa, Carlos E. Andrade, Mauricio G.C. Resende
This paper is a comprehensive literature review of Biased Random-Key Genetic Algorithms (BRKGA). BRKGA is a metaheuristic that employs random-key-based chromosomes with biased, uniform, and elitist mating strategies in a genetic algorithm framework. The review encompasses over 150 papers with a wide range of applications, including classical combinatorial optimization problems, real-world industrial
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The Impact of Platform’s Information Sharing on Manufacturer Encroachment and Selling Format Decision Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-25 Canran Gong, Joshua Ignatius, Huaming Song, Junwu Chai, Steven James Day
Motivated by recent practice observations, we consider an incumbent manufacturer who has an existing wholesale contract with an e-commerce platform, which the latter sells as a private label product in its online marketplace. In this context, the manufacturer launches its follower product, which will coexist alongside the private label product on the platform. We study the interplay between the manufacturer’s
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Vehicle routing with stochastic demand, service and waiting times — The case of food bank collection problems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-24 Meike Reusken, Gilbert Laporte, Sonja U.K. Rohmer, Frans Cruijssen
Food banks play an important role both in combating food waste, and in alleviating hunger. However, due to the many uncertainties that food banks face, they often struggle to effectively collect all food items that donors such as supermarkets are willing to provide. To tackle this problem, we introduce the capacitated vehicle routing problem with travel time restrictions and stochastic demand, service
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An efficient coalescent model for heterochronously sampled molecular data J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-20 Lorenzo Cappello, Amandine Véber, Julia A. Palacios
Molecular sequence variation at a locus informs about the evolutionary history of the sample and past population size dynamics. The Kingman coalescent is used in a generative model of molecular seq...
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Moments of the Nonnegative Adjusted Estimator of Squared Multiple Correlation Am. Stat. (IF 1.8) Pub Date : 2024-03-18 Joseph F. Lucke
I present the moments of the nonnegative adjusted estimator of the squared multiple correlation ρ2, the coefficient of determination for random-predictor regression. This estimator, first proposed...
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Extreme value statistics in semi-supervised models J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-21 Hanan Ahmed, John H.J. Einmahl, Chen Zhou
We consider extreme value analysis in a semi-supervised setting, where we observe, next to the n data on the target variable, n+m data on one or more covariates. This is called the semi-supervised...
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Corrigendum to “A New Formulation and a Branch-and-Cut Algorithm for the Set Orienteering Problem” [European Journal of Operational Research, Volume 314, Issue 2, 16 April 2024, Pages 446-465] Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-22 C. Archetti, F. Carrabs, R. Cerulli, F. Laureana
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Causal Effects of Time-Varying Exposures: A Comparison of Structural Equation Modeling and Marginal Structural Models in Cross-Lagged Panel Research Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-19 Jeroen D. Mulder, Kim Luijken, Bas B. L. Penning de Vries, Ellen L. Hamaker
The use of structural equation models for causal inference from panel data is critiqued in the causal inference literature for unnecessarily relying on a large number of parametric assumptions, and...
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Trust exploration- and leadership incubation- based opinion dynamics model for social network group decision-making: A quantum theory perspective Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-21 Peng Wang, Peide Liu, Yueyuan Li, Fei Teng, Witold Pedrycz
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Maximizing the net present value of a project under uncertainty: Activity delays and dynamic policies Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-20 Salim Rostami, Stefan Creemers, Roel Leus
We study a project with stochastic activity durations and cash flows; we model the uncertainty using discrete scenarios. The project entails precedence-related activities, each of which incurs a cash flow that may be positive (inflow) or negative (outflow). The problem is to find a scheduling policy that maximizes the expected net present value of the project. A scheduling policy decides the starting
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Frequency regulation with storage: On losses and profits Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-20 Dirk Lauinger, François Vuille, Daniel Kuhn
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Review of Practical Psychometrics: A Guide for Test Users Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-14 Musyaffa’ Ahmad, Muhammad Faisal
Published in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Bi-level optimisation of subsidy and capacity investment under competition and uncertainty Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-19 Zixuan Zhang, Michail Chronopoulos, Ioannis Kyriakou, Dimitrina S. Dimitrova
In this paper, we develop a bi-level real options framework for deriving the equilibrium Government subsidisation and firm-level capacity investment policy in a duopoly market structure. We find that strategic interactions with the Government may impact a firm’s capacity investment decision significantly and that the equilibrium subsidisation policy depends on both the market structure and the type
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Competition under demand uncertainty: The roles of technology and capacity strategy Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-19 Liu Yang, Chi To Ng, T.C.E. Cheng, Mingyao Sun, Xuefeng Shao, Ruiqing Li
To uncover the secrets of creating competitive advantage for firms under demand uncertainty, we study the roles of technology level and capacity investment strategies. Specifically, we analyze the Nash equilibrium of two competing firms at different technology levels under two capacity investment strategies, namely flexible or inflexible. We examine both symmetrical competition where the two firms
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Integer optimization models and algorithms for the multi-period non-shareable resource allocation problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-18 Jongyoon Park, Jinil Han, Kyungsik Lee
The resource allocation problem (RAP) determines a solution to optimally allocate limited resources to several activities or tasks. In this study, we propose a novel resource allocation problem referred to as multi-period non-shareable resource allocation problem (MNRAP), which is motivated by the characteristics of resources considered in the stem cell culture process for producing stem cell therapeutics
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50 years of warehousing research—An operations research perspective Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-18 Nils Boysen, René de Koster
Warehouses have always been an essential part of supply chains, but despite their fundamental role they were not seen as especially mission critical. With the advent of e-commerce, same-day deliveries, omni-channel retailing, and global supply chain disruptions, however, this assessment has changed, and today’s warehouses have evolved to technology-enriched fulfillment factories with strategic relevance
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Identifying Dynamic Shifts to Careless and Insufficient Effort Behavior in Questionnaire Responses; a Novel Approach and Experimental Validation Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-14 Zachary J. Roman, Patrick Schmidt, Jason M. Miller, Holger Brandt
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading t...
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Propensity score oversampling and matching for uplift modeling Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-16 Carla Vairetti, Franco Gennaro, Sebastián Maldonado
In this paper, we propose a novel matching strategy to correct for confounding in uplift modeling. Our method, called propensity score oversampling and matching (ProSOM), extends the well-known propensity score matching (PSM) technique by addressing one of its main limitations: dealing with small datasets that face an imbalance in the distribution of the causal variable. Apart from this, we also face
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A note on Steuer and Utz’s (2023) multi-objective optimization approach for generating sustainability-efficient fronts Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-16 Marcel Marohn, Benjamin R. Auer
Motivated by the increasing importance of sustainability in investing, Steuer and Utz (2023) propose a new approach for integrating environmental, social and governance (ESG) scores into the portfolio selection process. These authors claim that their multi-objective portfolio optimization problem always provides mean-variance-ESG-efficient solutions because it belongs to the class of -constraint problems
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Coordinating scheduling and rejection decisions in a two-machine flow shop scheduling problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-16 Dvir Shabtay, Enrique Gerstl
We study a two-machine flow shop scheduling problem where any operation can be rejected at a certain cost. A solution for such a problem requires two sets of decisions. The first involves the partition of the set of operations into two subsets: the set of operations that are accepted for scheduling in the shop, and the set of rejected operations. The second decision involves scheduling the set of accepted
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A survey of contextual optimization methods for decision-making under uncertainty Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-15 Utsav Sadana, Abhilash Chenreddy, Erick Delage, Alexandre Forel, Emma Frejinger, Thibaut Vidal
Recently there has been a surge of interest in operations research (OR) and the machine learning (ML) community in combining prediction algorithms and optimization techniques to solve decision-making problems in the face of uncertainty. This gave rise to the field of contextual optimization, under which data-driven procedures are developed to prescribe actions to the decision-maker that make the best