Applied Stochastic Models in Business and Industry最新文献

{"title":"Stochastic Modeling and Time-Frequency Analysis for Predictive Maintenance of Automotive Suspension Systems","authors":"Livio Fenga,&nbsp;Luca Biazzo","doi":"10.1002/asmb.70013","DOIUrl":"https://doi.org/10.1002/asmb.70013","url":null,"abstract":"<p>This article presents a real-time predictive maintenance model of vehicle suspensions based on vibration signal analysis. The study is grounded in the observation that suspension wear and failure are primarily driven by cumulative stresses and external shocks encountered during vehicle operation. We use a wavelet-based technique integrated with stochastic modeling and lifetime data analysis to predict the remaining useful life (RUL) of the suspension. The proposed framework provides a decision-making tool for determining whether and when suspension systems should be subjected to inspection, replacement, or overhaul. An empirical application, using vibration data from a uniaxial accelerometer mounted on a vehicle suspension under varying road conditions, validates the theoretical model and estimation procedure.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foreword to the Special Issue on Data Science in Business and Industry","authors":"David Banks,&nbsp;Alba Martínez-Ruiz,&nbsp;David F. Muñoz,&nbsp;Javier Trejos-Zelaya","doi":"10.1002/asmb.70019","DOIUrl":"https://doi.org/10.1002/asmb.70019","url":null,"abstract":"","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feature Selection for Stock Movement Direction Prediction Using Sparse Support Vector Machine","authors":"Maoxuan Miao,&nbsp;Jinran Wu,&nbsp;Fengjing Cai,&nbsp;Liya Fu,&nbsp;Shurong Zheng,&nbsp;You-Gan Wang","doi":"10.1002/asmb.70011","DOIUrl":"https://doi.org/10.1002/asmb.70011","url":null,"abstract":"&lt;p&gt;In financial markets, accurate stock price movement prediction can significantly enhance investors' profits. However, the stock price is a highly complex dynamic system with considerable fluctuations, and the accuracy of direction prediction can be improved by selecting appropriate technical indicators. In this work, we propose a novel sparse support vector machines (SVMs) that combines recursive feature elimination (RFE) and ReliefF using a weight parameter. Unlike traditional RFE-based SVMs, our approach constructs a nested feature subset structure, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;F&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;⊂&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;F&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;⊂&lt;/mo&gt;\u0000 &lt;mi&gt;⋯&lt;/mi&gt;\u0000 &lt;mo&gt;⊂&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;F&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;p&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {F}_1subset {F}_2subset cdots subset {F}_p $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, using a new filter algorithm that combines backward sacrifice and ReliefF by weighting. This new filter algorithm can capture relevant features and feature interactions simultaneously and is crucial in preventing valuable features from being removed at each iteration. Moreover, the ReliefF algorithm combined with RFE can identify more discriminative feature subsets by reordering the features such that valuable ones are ranked higher than valueless ones, and removing valueless features sequentially through iterative processes. Our experimental results on nine stock datasets from the liquor and spirits concept demonstrate that our proposed method outperforms baseline sparse SVMs and SVM models in terms of accuracy and F-test, while also producing a desirable number of features and automatically eliminating redundancy among technical indicators. We also show that on most stock datasets, the ReliefF algorithm combined with RFE can effectively identify discriminative feature subsets for cases of linear and Gaussian kernel SVMs and our proposed filter method can prevent valuable features from being removed at each iteration. In addition, our experimental findings reveal that feature subsets generated by technical indicators are more discriminative while feature subsets generated by technical i","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144091865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian Hierarchical Modeling of Noisy Gamma Processes: Formulation and Extensions for Unit-To-Unit Variability","authors":"Ryan Leadbetter,&nbsp;Gabriel González Cáceres,&nbsp;Aloke Phatak","doi":"10.1002/asmb.70014","DOIUrl":"https://doi.org/10.1002/asmb.70014","url":null,"abstract":"<p>The gamma process is a natural model for monotonic degradation processes. In practice, it is desirable to extend the single gamma process to incorporate measurement error and to construct models for the degradation of several nominally identical units. In this paper, we show how these extensions are easily facilitated through the Bayesian hierarchical modeling framework. Following the precepts of the Bayesian statistical workflow, we show the principled construction of a noisy gamma process model. We also reparameterise the gamma process to simplify the specification of priors and make it obvious how the single gamma process model can be extended to include unit-to-unit variability or covariates. We first fit the noisy gamma process model to a single simulated degradation trace. In doing so, we find an identifiability problem between the volatility of the gamma process and the measurement error when there are only a few noisy degradation observations. However, this lack of identifiability can be resolved by including extra information in the analysis through a stronger prior or extra data that informs one of the non-identifiable parameters, or by borrowing information from multiple units. We then explore extensions of the model to account for unit-to-unit variability and demonstrate them using a crack-propagation data set with added measurement error. Lastly, we perform model selection in a fully Bayesian framework by using cross-validation to approximate the expected log probability density of a new observation. We also show how failure time distributions with uncertainty intervals can be calculated for new units or units that are currently under test but have yet to fail.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industrial Statistics in the Knowledge Economy","authors":"David Banks,&nbsp;Yue Li","doi":"10.1002/asmb.70018","DOIUrl":"https://doi.org/10.1002/asmb.70018","url":null,"abstract":"<div>\u0000 \u0000 <p>Industrial statistics grew up in an era when manufacturing was the primary engine of commerce. Today, the driver is information technology. This paper discusses how statisticians need to adapt to contribute to this new business model, with particular emphasis upon computational advertising, autonomous vehicles, operations management, and large language models. Remarkably, many of our old tools are still relevant, even as the new problem space poses fresh research challenges for our employment and educational systems.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multistate Markovian Model of the Economic Burden for Allergy Immunotherapy","authors":"Massimo Bilancia,&nbsp;Gaetano Serviddio","doi":"10.1002/asmb.70017","DOIUrl":"https://doi.org/10.1002/asmb.70017","url":null,"abstract":"<div>\u0000 \u0000 <p>The incidence of allergic rhinoconjunctivitis due to pollinosis is increasing in Western countries. The first-line therapy (No-AIT) typically involves the administration of antihistamines and corticosteroid sprays to manage symptoms. Immunotherapy represents an alternative treatment option, as it promotes desensitization to allergens. However, it is associated with significant costs. Currently, two types of allergen immunotherapy (AIT) are prescribed: subcutaneous immunotherapy and sublingual immunotherapy. This article compares these two therapeutic options with No-AIT. The comparison is conducted through a cost-effectiveness analysis (CEA), which evaluates health-related outcomes by estimating the incremental cost per unit of change in a composite outcome that combines morbidity and quality-of-life metrics. To perform the analysis, we developed a realistic multistate model describing the progression of a cohort of patients undergoing the three therapeutic approaches. The model was designed to be sufficiently flexible to account for treatment-related challenges commonly observed in real-world settings, which are often inadequately represented in randomized controlled trials. By employing a novel two-dimensional framework, we tracked the proportion of the cohort transitioning between health states during each cycle while simultaneously capturing the origin and destination of each transition. This approach enabled the integration of structural features that are typically overlooked, such as early treatment discontinuation, transition rewards, nonstationarities associated with the usual termination of immunotherapy after three years, and differential protection against severe complications (e.g., asthma) depending on whether immunotherapy was completed or not. Deterministic simulations were conducted using standard input parameters, supplemented by probabilistic simulations to generate CEACs for each of the three strategies. The results from our model indicate that AIT is not cost-effective unless the payer exhibits a moderately high willingness-to-pay. These findings have important implications for the pharmaceutical industry involved in the production of AIT drugs.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soft-Clipping Autoregressive Models for Ordinal Time Series","authors":"Christian H. Weiß,&nbsp;Osama Swidan","doi":"10.1002/asmb.70015","DOIUrl":"https://doi.org/10.1002/asmb.70015","url":null,"abstract":"<p>The linear autoregressive models are among the most popular models in the practice of time series analysis, which constitutes an incentive to adapt them to ordinal time series as well. Our starting point for modeling ordinal time series data is the latent variable approach to define a generalized linear model. This method, however, typically leads to a non-linear relationship between the past observations and the current conditional cumulative distribution function (cdf). To overcome this problem, we use the soft-clipping link to obtain an approximately linear model structure and propose a wide and flexible class of soft-clipping autoregressive (scAR) models. The constraints imposed on the model parameters allow us to identify relevant special cases of the scAR model family. We study the calculation of transition probabilities as well as approximate formulae for the CDF. Our proposals are illustrated by numerical examples and simulation experiments, where the performance of maximum likelihood estimation as well as model selection is analyzed. The novel model family is successfully applied to a real-world ordinal time series from finance.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143909248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated Optimization of Pricing, Maintenance Strategies, and Market Coverage: A Bargaining Model for Full-Service Contracts With Loss-Averse Participants","authors":"Ali Farrokhi-Sefat,&nbsp;Mohammad Sheikhalishahi,&nbsp;Ata Allah Taleizadeh","doi":"10.1002/asmb.70005","DOIUrl":"https://doi.org/10.1002/asmb.70005","url":null,"abstract":"<div>\u0000 \u0000 <p>As industries increasingly outsource their Maintenance, Repair, and Overhaul (MRO) programs to third-party service providers, Original Equipment Manufacturers (OEMs) seek to expand their market share by providing comprehensive MRO packages along with the original products at a bundled price. This study introduces a bargaining model that jointly optimizes pricing, maintenance policies, and OEM's market coverage, considering participants' gain/loss behaviors within the Full-Service Product System (FSPS) contracts framework. We first provide closed-form analysis for various scenarios in a one-on-one bargaining negotiation, resulting in significant computational efficiency and insightful managerial implications. It also enables us to expand the problem to multiple contracts and develop an algorithm that simultaneously optimizes client density, profitability, pricing and MRO policies. The findings indicate that when players' profits fall short of their reference point, a more loss-averse approach results in increased personal profit and less favorable outcomes for the opponent. We further enrich our findings by conducting a sensitivity analysis of the parameters affecting the pricing, MRO policies, and market coverage.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143884064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Latent Risk Based on Joint Modelling of Multiple Health Insurance Outcomes of Mixed Types","authors":"Xingde Duan,&nbsp;Renjun Ma","doi":"10.1002/asmb.70012","DOIUrl":"https://doi.org/10.1002/asmb.70012","url":null,"abstract":"<p>Our research is motivated by an insurance study involving 788 insurance subscribers who made claims resulting from ischemic heart disease. Four different types of health services used by these subscribers as well as the corresponding total cost were observed for two years. Health care utilizations vary a lot even for subscribers of the same personal characteristics. The research question of primary interest is how to capture patient-specific latent risks beyond what can be explained by known personal characteristics. In this study, we characterize unobserved latent risks by random effects in our joint Tweedie mixed models for multiple health outcomes of mixed types. An optimal estimation of our model has been developed using the orthodox best linear unbiased predictors of random effects. Our approach is illustrated with the analysis of the health insurance study of 788 ischemic heart disease patients. Applying cluster analysis to the patient-specific latent risks predicted by our model, we were able to classify patients into a high risk group of 36 patients, a medium risk group of 256 patients and a low risk group of 496 patients. The finding is of important policy relevance since the losses suffered by a few are known to be spread over many in an insurance system. Grouping of patients and prioritization of specific groups based on subject-specific latent risks facilitates resource allocation and pricing.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing Accelerated Degradation Tests Based on Wiener Process With a Positive Relation Between the Drift Rate and the Volatility","authors":"Daojiang He,&nbsp;Lei He,&nbsp;Jinming Ren","doi":"10.1002/asmb.70010","DOIUrl":"https://doi.org/10.1002/asmb.70010","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we study the optimal design problem for constant-stress accelerated degradation tests using a new class of Wiener processes that effectively capture the positive relation between the drift rate and the volatility. Under the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>D</mi>\u0000 </mrow>\u0000 <annotation>$$ D $$</annotation>\u0000 </semantics></math>-, <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>A</mi>\u0000 </mrow>\u0000 <annotation>$$ A $$</annotation>\u0000 </semantics></math>-, and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>c</mi>\u0000 </mrow>\u0000 <annotation>$$ c $$</annotation>\u0000 </semantics></math>-optimality criteria, both the test stress levels and the allocation of test units at each stress level are explicitly determined. We provide a numerical example using carbon-film resistor data to validate our theoretical findings and perform a simulation study to highlight the advantages of our proposed designs. The numerical results suggest that the proposed designs outperform existing designs in terms of estimation accuracy.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143801700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}