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Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov process J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-09-18 Akihiko Nishimura, Zhenyu Zhang, Marc A. Suchard
Zigzag and other piecewise deterministic Markov process samplers have attracted significant interest for their non-reversibility and other appealing properties for Bayesian posterior computation. H...
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Valid Inference After Causal Discovery J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-09-17 Paula Gradu, Tijana Zrnic, Yixin Wang, Michael I. Jordan
Causal discovery and causal effect estimation are two fundamental tasks in causal inference. While many methods have been developed for each task individually, statistical challenges arise when app...
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An effective and small sample-size valid confidence interval for isotonic dose-response curves by inverting a partial likelihood ratio test Am. Stat. (IF 1.8) Pub Date : 2024-09-19 J. G. Liao
A dose-response curve is essential for determining the safe dosage of a drug and is widely used in bioassay and in phase 1 clinical trials. It is generally accepted that the probability of death or...
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Off-policy Evaluation in Doubly Inhomogeneous Environments J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-09-09 Zeyu Bian, Chengchun Shi, Zhengling Qi, Lan Wang
This work aims to study off-policy evaluation (OPE) under scenarios where two key reinforcement learning (RL) assumptions – temporal stationarity and individual homogeneity are both violated. To ha...
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An indifference result for social choice rules in large societies Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-12 Dezső Bednay, Balázs Fleiner, Attila Tasnádi
Social choice rules can be defined or derived by minimizing distance-based objective functions. One problem with this approach is that any social choice rule can be derived by selecting an appropriate distance function. Another problem comes from the computational difficulty of determining the solution of some social choice rules. We provide a general positive indifference result when looking at expected
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Estimation of Contact Time Among Animals from Telemetry Data Am. Stat. (IF 1.8) Pub Date : 2024-09-09 Andrew B. Whetten, Trevor J. Hefley, David A. Haukos
Continuous processes in most applications are measured discretely with error. This complicates the task of detecting intersections and the number of intersections between two continuous processes (...
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Measuring the Functioning Human Brain Annu. Rev. Stat. Appl. (IF 7.4) Pub Date : 2024-09-11 Martin A. Lindquist, Bonnie B. Smith, Arunkumar Kannan, Angela Zhao, Brian Caffo
The emergence of functional magnetic resonance imaging (fMRI) marked a significant technological breakthrough in the real-time measurement of the functioning human brain in vivo. In part because of their 4D nature (three spatial dimensions and time), fMRI data have inspired a great deal of statistical development in the past couple of decades to address their unique spatiotemporal properties. This
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High-Dimensional Gene–Environment Interaction Analysis Annu. Rev. Stat. Appl. (IF 7.4) Pub Date : 2024-09-11 Mengyun Wu, Yingmeng Li, Shuangge Ma
Beyond the main genetic and environmental effects, gene–environment (G–E) interactions have been demonstrated to significantly contribute to the development and progression of complex diseases. Published analyses of G–E interactions have primarily used a supervised framework to model both low-dimensional environmental factors and high-dimensional genetic factors in relation to disease outcomes. In
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Assessing Heterogeneity of Correlation Matrices in Misspecified Meta-Analytic Structural Equation Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-09 Christian Bloszies, Tobias Koch
Meta-analytic structural equation modeling (MASEM) techniques are increasingly common tools to synthesize data across multiple studies. One popular approach is two-step MASEM, where study correlati...
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Condition-based switching, loading, and age-based maintenance policies for standby systems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-10 Xian Zhao, Rong Li, He Han, Qingan Qiu
Standby techniques are widely incorporated in structural design to enhance the inherent reliability of systems. To further leverage the system performance during operation, decision-makers can adopt operational policies to manage system degradation. Specifically, at the system level, unit switching that dynamically determines the online unit contributes to avoiding unexpected shutdowns. At the unit
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A newsvendor model with multiple reference points: Target-setting for aspirational newsvendors Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-10 Tian Bai, Gengzhong Feng, Meng Wu, Stuart X. Zhu
Prospect theory posits that the determination of an outcome as a gain or loss hinges upon the reference points, thereby exerting a substantial influence on the decision-making processes of individuals. These reference points can encompass both external targets and internal aspirations (self-goals), forming two potential candidates. Despite a growing body of evidence showcasing the concurrent impact
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Overseas production or domestic production? Impacts of tax disparity and market difference Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-07 Baozhuang Niu, Nan Zhang, Zihao Mu
Overseas and domestic production are two commonly employed strategies for multinational firms (MNFs) to manage their global production operations. Recent tax-cutting initiatives have made domestic production an attractive option for MNFs. We aim to investigate whether such initiatives can effectively induce MNFs to produce domestically, especially when they cater to both domestic and foreign markets
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Equilibrium analysis of the seller’s fulfillment channels and sales channels Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-07 Shu Hu, Ke Fu
Sellers’ products can be sold either through platform channels or through their own channels. Also, sellers’ orders can either be fulfilled by platforms (FBP) or be fulfilled by third-party merchants (FBM). We consider a platform and a representative seller that compete in selling two substitutable products. We develop an analytical framework for identifying each firm’s structure preference by comparing
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New Developments in Measurement Invariance Testing: An Overview and Comparison of EFA-Based Approaches Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05 Philipp Sterner, Kim De Roover, David Goretzko
When comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently...
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Deriving Expected Values of Model Parameters When Using Sum Scores in Simulation Research Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05 A. R. Georgeson
There is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from ...
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Efficient Adjusted Joint Significance Test and Sobel-Type Confidence Interval for Mediation Effect Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-04 Haixiang Zhang
Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of th...
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A fused large language model for predicting startup success Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Abdurahman Maarouf, Stefan Feuerriegel, Nicolas Pröllochs
Investors are continuously seeking profitable investment opportunities in startups and, hence, for effective decision-making, need to predict a startup’s probability of success. Nowadays, investors can use not only various fundamental information about a startup (e.g., the age of the startup, the number of founders, and the business sector) but also textual description of a startup’s innovation and
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Retailer’s information sharing and manufacturer’s channel expansion in the live-streaming E-commerce era Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Wei Lu, Xiang Ji, Jie Wu
Numerous manufacturers started to embrace live-streaming selling channels in addition to their preexisting retail channels during the outbreak of COVID-19. Our work investigates a retailer’s optimal strategy for sharing demand information with a manufacturer who may collaborate with a streamer to build a live-streaming selling channel. The results indicate that the manufacturer’s live-streaming selling
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Addressing the multiplicity of optimal solutions to the Clonal Deconvolution and Evolution Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Maitena Tellaetxe-Abete, Charles Lawrie, Borja Calvo
The Clonal Deconvolution and Evolution Problem consists on unraveling the clonal structure and phylogeny of a tumor using estimated mutation frequency values obtained from multiple biopsies containing mixtures of tumor clones. In this article, we tackle the problem from an optimization perspective and we explore the number of optimal solutions for a given instance. Even in ideal scenarios without noise
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Moderate exponential-time quantum dynamic programming across the subsets for scheduling problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-05 Camille Grange, Michael Poss, Eric Bourreau, Vincent T’kindt, Olivier Ploton
Grover Search is currently one of the main quantum algorithms leading to hybrid quantum–classical methods that reduce the worst-case time complexity for some combinatorial optimization problems. Specifically, the combination of Quantum Minimum Finding (obtained from Grover Search) with dynamic programming has proved particularly efficient in improving the complexity of NP-hard problems currently solved
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A Structural After Measurement Approach to Bifactor Predictive Models Struct. Equ. Model. (IF 2.5) Pub Date : 2024-09-05 Jinsoo Choi, Sunbeom Kwon, Bo Zhang
The bifactor model is becoming a popular tool for modeling hierarchical constructs. However, the bifactor predictive model, which uses both the general factor and all group factors to predict a cri...
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Quadratic horizontally elastic not-first/not-last filtering algorithm for cumulative constraint Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-03 Roger Kameugne, Sévérine Fetgo Betmbe, Thierry Noulamo
The not-first/not-last rule is a pendant of the edge finding rule, generally embedded in the constraint during constraint-based scheduling. It is combined with other filtering rules for more pruning of the tree search. In this paper, the data structure in which tasks are scheduled in a horizontally elastic way is used to strengthen the classic not-first/not-last rule. Potential not-first task intervals
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Measures of stochastic non-dominance in portfolio optimization Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-03 Jana Junová, Miloš Kopa
Stochastic dominance rules are well-characterized and widely used. This work aims to describe and better understand the situations when they do not hold by developing measures of stochastic non-dominance. They quantify the error caused by assuming that one random variable dominates another one when it does not. To calculate them, we search for a hypothetical random variable that satisfies the stochastic
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Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-09-03 Steve Yadlowsky, Scott Fleming, Nigam Shah, Emma Brunskill, Stefan Wager
There are a number of available methods for selecting whom to prioritize for treatment, including ones based on treatment effect estimation, risk scoring, and hand-crafted rules. We propose rank-we...
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End-to-end, decision-based, cardinality-constrained portfolio optimization Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-02 Hassan T. Anis, Roy H. Kwon
Portfolios employing a (factor) risk model are usually constructed using a two step process: first, the risk model parameters are estimated, then the portfolio is constructed. Recent works have shown that this decoupled approach may be improved using an integrated framework that takes the downstream portfolio optimization into account during parameter estimation. In this work we implement an integrated
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Model-based causal feature selection for general response types J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-30 Lucas Kook, Sorawit Saengkyongam, Anton Rask Lundborg, Torsten Hothorn, Jonas Peters
Discovering causal relationships from observational data is a fundamental yet challenging task. Invariant causal prediction (ICP, Peters et al., 2016) is a method for causal feature selection which...
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Explainable profit-driven hotel booking cancellation prediction based on heterogeneous stacking-based ensemble classification Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-31 Zhenkun Liu, Koen W. De Bock, Lifang Zhang
The goal of hotel booking cancellation prediction in the hospitality industry is to identify potential cancellations from a large customer base and improve the efficiency of customer retention and capacity management efforts. Whilst prior research has shown that the predictive performance of hotel booking cancellation prediction can be further enhanced by integrating multiple classifiers, the explainability
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Industry return prediction via interpretable deep learning Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-31 Lazaros Zografopoulos, Maria Chiara Iannino, Ioannis Psaradellis, Georgios Sermpinis
We apply an interpretable machine learning model, the LassoNet, to forecast and trade U.S. industry portfolio returns. The model combines a regularization mechanism with a neural network architecture. A cooperative game-theoretic algorithm is also applied to interpret our findings. The latter hierarchizes the covariates based on their contribution to the overall model performance. Our findings reveal
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Integration of prediction and optimization for smart stock portfolio selection Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-30 Puja Sarkar, Vivekanand B. Khanapuri, Manoj Kumar Tiwari
Machine learning (ML) algorithms pose significant challenges in predicting unknown parameters for optimization models in decision-making scenarios. Conventionally, prediction models are optimized independently in decision-making processes, whereas ML algorithms primarily focus on minimizing prediction errors, neglecting the role of decision-making in downstream optimization tasks. The pursuit of high
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Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-30 Lucas Vogels, Reza Mohammadi, Marit Schoonhoven, Ş. İlker Birbil
Gaussian graphical models provide a powerful framework to reveal the conditional dependency structure between multivariate variables. The process of uncovering the conditional dependency network is...
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Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-30 Ross L. Prentice
Published in Journal of the American Statistical Association (Just accepted, 2024)
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Asymptotically optimal energy consumption and inventory control in a make-to-stock manufacturing system Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Erhun Özkan, Barış Tan
We study a make-to-stock manufacturing system in which a single server makes the production. The server consumes energy, and its power consumption depends on the server state: a busy server consumes more power than an idle server, and an idle server consumes more power than a turned-off server. When a server is turned on, it completes a costly set-up process that lasts a while. We jointly control the
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An optimization framework for solving large scale multidemand multidimensional knapsack problem instances employing a novel core identification heuristic Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Sameh Al-Shihabi
By applying the core concept to solve a binary integer program (BIP), certain variables of the BIP are fixed to their anticipated values in the optimal solution. In contrast, the remaining variables, called core variables, are used to construct and solve a core problem (CP) instead of the BIP. A new approach for identifying CP utilizing a local branching (LB) alike constraint is presented in this article
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Multiple financial analyst opinions aggregation based on uncertainty-aware quality evaluation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Shuai Jiang, Wenjun Zhou, Yanhong Guo, Hui Xiong
Financial analysts’ opinions are pivotal in investment decision-making, as they provide valuable expert knowledge. Aggregating these opinions offers a promising way to unlock their collective wisdom. However, existing opinion aggregation methods are hindered by their inability to effectively assess differences in opinion quality, resulting in suboptimal outcomes. This Study introduces a novel model
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Monte Carlo inference for semiparametric Bayesian regression J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-28 Daniel R. Kowal, Bohan Wu
Data transformations are essential for broad applicability of parametric regression models. However, for Bayesian analysis, joint inference of the transformation and model parameters typically invo...
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The circular balancing problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-24 Myungho Lee, Kangbok Lee, Michael Pinedo
We propose a balancing problem with a minmax objective in a circular setting. This balancing problem involves the arrangement of an even number of items with different weights on a circle while minimizing the maximum total weight of items arranged on any half circle. Due to its generic structure, it may have applications in fair resource allocation schemes. We show the NP-hardness of the problem and
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Fair integer programming under dichotomous and cardinal preferences Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-24 Tom Demeulemeester, Dries Goossens, Ben Hermans, Roel Leus
One cannot make truly fair decisions using integer linear programs unless one controls the selection probabilities of the (possibly many) optimal solutions. For this purpose, we propose a unified framework when binary decision variables represent agents with preferences, who only care about whether they are selected in the final solution. We develop several general-purpose algorithms to fairly select
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A multiobjective [formula omitted]-constraint based approach for the robust master surgical schedule under multiple uncertainties Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-23 Salma Makboul, Alexandru-Liviu Olteanu, Marc Sevaux
The efficient scheduling of elective surgeries in hospitals is critical for ensuring patient satisfaction, cost-effectiveness, and overall operational efficiency. However, operating theater (OT) managers face complex and competing scheduling problems due to numerous sources of uncertainty and the impact of the proposed schedule on downstream recovery units, such as the intensive care unit (ICU). To
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Evaluation of counterparty credit risk under netting agreements Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-23 Ahmadreza Tavasoli, Michèle Breton
We investigate counterparty credit risk and credit valuation adjustments in portfolios including derivatives with early-exercise opportunities, under a netting agreement. We show that credit risk and netting agreements have a significant impact on the way portfolios are managed (that is, on options’ exercise strategies) and, therefore, on the value of the portfolio and on the price of counterparty
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Maintenance optimization for multi-component systems with a single sensor Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Ragnar Eggertsson, Ayse Sena Eruguz, Rob Basten, Lisa M. Maillart
We consider a multi-component system in which a single sensor monitors a condition parameter. Monitoring gives the decision maker partial information about the system state, but it does not reveal the exact state of the components. Each component follows a discrete degradation process, possibly correlated with the degradation of other components. The decision maker infers a belief about each component’s
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A framework for integrated resource planning in surgical clinics Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Thomas Reiten Bovim, Anders N. Gullhav, Henrik Andersson, Atle Riise
The problem under study is based on the challenges faced by the Orthopaedic Clinic at St. Olav’s Hospital in Trondheim, Norway. Variations in demand and supply cause fluctuating waiting lists, and it is challenging to level the activities between the clinic’s two units, the outpatient clinic and the operating theater, to obtain short waiting times for all activities. Based on these challenges, we describe
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Applying fixed order commitment contracts in a capacitated supply chain Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Christina Imdahl, Kai Hoberg, William Schmidt
Demand uncertainty can lead to excess inventory holdings, capacity creation, emergency deliveries, and stock-outs. The costs of demand uncertainty may be directly borne by upstream suppliers, but can propagate downstream in the form of higher prices. To address these problems, we investigate a practical application of a fixed order commitment contract (FOCC) in which a manufacturer commits to a minimum
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Semi-supervised Triply Robust Inductive Transfer Learning J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-22 Tianxi Cai, Mengyan Li, Molei Liu
In this work, we propose a Semi-supervised Triply Robust Inductive transFer LEarning (STRIFLE) approach, which integrates heterogeneous data from a label-rich source population and a label-scarce t...
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Natural Gradient Variational Bayes without Fisher Matrix Analytic Calculation and Its Inversion J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-22 A. Godichon-Baggioni, D. Nguyen, M-N. Tran
This paper introduces a method for efficiently approximating the inverse of the Fisher information matrix, a crucial step in achieving effective variational Bayes inference. A notable aspect of our...
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Statistical Inference for Networks of High-Dimensional Point Processes J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-22 Xu Wang, Mladen Kolar, Ali Shojaie
Fueled in part by recent applications in neuroscience, the multivariate Hawkes process has become a popular tool for modeling the network of interactions among high-dimensional point process data. ...
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Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-22 Reza Mohammadi
Published in Journal of the American Statistical Association (Vol. 119, No. 547, 2024)
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A Theoretical Review of Modern Robust Statistics Annu. Rev. Stat. Appl. (IF 7.4) Pub Date : 2024-08-21 Po-Ling Loh
Robust statistics is a fairly mature field that dates back to the early 1960s, with many foundational concepts having been developed in the ensuing decades. However, the field has drawn a new surge of attention in the past decade, largely due to a desire to recast robust statistical principles in the context of high-dimensional statistics. In this article, we begin by reviewing some of the central
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Crafting 10 Years of Statistics Explanations: Points of Significance Annu. Rev. Stat. Appl. (IF 7.4) Pub Date : 2024-08-21 Naomi Altman, Martin Krzywinski
Points of Significance is an ongoing series of short articles about statistics in Nature Methods that started in 2013. Its aim is to provide clear explanations of essential concepts in statistics for a nonspecialist audience. The articles favor heuristic explanations and make extensive use of simulated examples and graphical explanations, while maintaining mathematical rigor. Topics range from basic
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Portfolio default losses driven by idiosyncratic risks Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-21 Shaoying Chen, Zhiwei Tong, Yang Yang
We consider a portfolio of general defaultable assets with low individual default risk and study the probability of the portfolio default loss exceeding an arbitrary threshold. The latent variables driving defaults are modeled by a mixture structure that combines common shock, systematic risk, and idiosyncratic risk factors. While common shocks and systematic risk have been found by many studies to
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Tightening Blocks in Complementary Analyses of Observational Studies: Optimization Algorithm and Examples Am. Stat. (IF 1.8) Pub Date : 2024-08-20 Paul R. Rosenbaum
An observational block design has I blocks matched for covariates and J individuals per block, but treatments were not randomly assigned to individuals within blocks, as would have been done in an ...
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Statistical Data Integration for Health Policy Evidence-Building Annu. Rev. Stat. Appl. (IF 7.4) Pub Date : 2024-08-19 Susan M. Paddock, Carolina Franco, F. Jay Breidt, Brenda Betancourt
Health policy evidence-building requires data sources such as health care claims, electronic health records, probability and nonprobability survey data, epidemiological surveillance databases, administrative data, and more, all of which have strengths and limitations for a given policy analysis. Data integration techniques leverage the relative strengths of input sources to obtain a blended source
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Exact and heuristic approaches for the ship-to-shore problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-19 M. Wagenvoort, P.C. Bouman, M. van Ee, T. Lamballais Tessensohn, K. Postek
After a natural disaster such as a hurricane or flooding, the navy can help by bringing supplies, clearing roads, and evacuating victims. If destinations cannot be reached over land, resources can be transported using smaller ships and helicopters, called connectors. To start aid on land as soon as possible this must be done efficiently. In the ship-to-shore problem, trips with their accompanying resources
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Efficient Multiple Change Point Detection and Localization For High-dimensional Quantile Regression with Heteroscedasticity J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-19 Xianru Wang, Bin Liu, Xinsheng Zhang, Yufeng Liu
Data heterogeneity is a challenging issue for modern statistical data analysis. There are different types of data heterogeneity in practice. In this paper, we consider potential structural changes ...
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Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-14 Rupam Bhattacharyya, Nicholas C. Henderson, Veerabhadran Baladandayuthapani
Rapid advancements in collection and dissemination of multi-platform molecular and genomics data has resulted in enormous opportunities to aggregate such data in order to understand, prevent, and t...
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Parallel sampling of decomposable graphs using Markov chains on junction trees J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-14 Mohamad Elmasri
Bayesian inference for undirected graphical models is mostly restricted to the class of decomposable graphs, as they enjoy a rich set of properties making them amenable to high-dimensional problems...
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Customer and provider bounded rationality in on-demand service platforms Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-17 Danna Chen, Yong-Wu Zhou, Xiaogang Lin, Kangning Jin
The growing literature on operations management in the context of the sharing economy typically assumes that both customers and providers are fully rational. In contrast, we consider an on-demand service platform (e.g., Didi and Uber) with boundedly rational customers and providers that sets a price charged to customers and a wage paid to providers. Both customers and providers are sensitive to the
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Optimal payoffs under smooth ambiguity Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-17 An Chen, Steven Vanduffel, Morten Wilke
We study optimal payoff choice for an investor in a one-period model under smooth ambiguity preferences, also called as proposed by Klibanoff et al. (2005). In contrast to the existing literature on optimal asset allocation for a KMM investor in a one-period model, we also allow payoffs that are non-linear in the market asset. Our contribution is fourfold. First, we characterize and derive the optimal
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Corrigendum to “Labeling methods for partially ordered paths” [European Journal of Operational Research 318 (2024) 19–30] Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-16 Ricardo Euler, Pedro Maristany de las Casas
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Optimal Network Membership Estimation under Severe Degree Heterogeneity J. Am. Stat. Assoc. (IF 3.0) Pub Date : 2024-08-13 Zheng Tracy Ke, Jingming Wang
Real networks often have severe degree heterogeneity, with maximum, average, and minimum node degrees differing significantly. This paper examines the impact of degree heterogeneity on statistical ...
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An unified framework for measuring environmentally-adjusted productivity change: Theoretical basis and empirical illustration Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-14 A. Abad, P. Ravelojaona
This paper aims to define an unified framework to analyse environmentally-adjusted productivity change. Equivalence conditions for additive and multiplicative environmentally-adjusted productivity indicators and indices are highlighted. Besides, an empirical illustration is provided considering non parametric convex neutral by-production model.