Applied Stochastic Models in Business and Industry最新文献_第5页

Modeling multivariate positive-valued time series using R-INLA 使用 R-INLA 建立多元正值时间序列模型

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-28 DOI: 10.1002/asmb.2834

Chiranjit Dutta, Nalini Ravishanker, Sumanta Basu

引用次数: 0

Multivariate simulation-based forecasting for intraday power markets: Modeling cross-product price effects 基于多变量模拟的盘中电力市场预测：跨产品价格效应建模

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-25 DOI: 10.1002/asmb.2837

Simon Hirsch, Florian Ziel

{"title":"Multivariate simulation-based forecasting for intraday power markets: Modeling cross-product price effects","authors":"Simon Hirsch, Florian Ziel","doi":"10.1002/asmb.2837","DOIUrl":"https://doi.org/10.1002/asmb.2837","url":null,"abstract":"Intraday electricity markets play an increasingly important role in balancing the intermittent generation of renewable energy resources, which creates a need for accurate probabilistic price forecasts. However, research to date has focused on univariate approaches, while in many European intraday electricity markets all delivery periods are traded in parallel. Thus, the dependency structure between different traded products and the corresponding cross-product effects cannot be ignored. We aim to fill this gap in the literature by using copulas to model the high-dimensional intraday price return vector. We model the marginal distribution as a zero-inflated Johnson's <math altimg=\"urn:x-wiley:asmb:media:asmb2837:asmb2837-math-0001\" display=\"inline\" location=\"graphic/asmb2837-math-0001.png\" overflow=\"scroll\">\u0000<semantics>\u0000<mrow>\u0000<msub>\u0000<mrow>\u0000<mi>S</mi>\u0000</mrow>\u0000<mrow>\u0000<mi>U</mi>\u0000</mrow>\u0000</msub>\u0000</mrow>\u0000$$ {S}_U $$</annotation>\u0000</semantics></math> distribution with location, scale, and shape parameters that depend on market and fundamental data. The dependence structure is modeled using copulas, accounting for the particular market structure of the intraday electricity market, such as overlapping but independent trading sessions for different delivery days and allowing the dependence parameter to be time-varying. We validate our approach in a simulation study for the German intraday electricity market and find that modeling the dependence structure improves the forecasting performance. Additionally, we shed light on the impact of the single intraday coupling on the trading activity and price distribution and interpret our results in light of the market efficiency hypothesis. The approach is directly applicable to other European electricity markets.","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139583743","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}

引用次数: 0

Messages from the outgoing and incoming Editor-in-Chiefs 即将离任和继任主编的致辞

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-21 DOI: 10.1002/asmb.2845

Fabrizio Ruggeri, Nalini Ravishanker

引用次数: 0

Linkage vector autoregressive model 联系向量自回归模型

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-16 DOI: 10.1002/asmb.2842

Manabu Asai, Mike K. P. So

{"title":"Linkage vector autoregressive model","authors":"Manabu Asai, Mike K. P. So","doi":"10.1002/asmb.2842","DOIUrl":"10.1002/asmb.2842","url":null,"abstract":"<p>To accommodate linkage effects of individuals, we develop a new linkage vector autoregressive (LAR) model for dynamic panel data. A main feature of the LAR model is incorporating dynamic network information in autoregressive time series modeling. The dynamic network can be given, or we can formulate the network links as a function of historical data, where unknown parameters of the function can be estimated from the data. We propose a simulation technique to check the stationarity condition of the LAR model and suggest a Bayesian Markov chain Monte Carlo method for estimation. Empirical results for the quarterly growth rates of gross domestic product (GDP) in 45 countries indicate that (i) the autoregressive (AR) coefficient for the aggregated growth rate is hard to distinguish from zero; (ii) a panel AR model with individual effects has a positive autocorrelation; and (iii) the alternative LAR models are preferred to the panel AR model. Depending on the specification of the linkage variables, the sign and size of the linkage effect can differ. The logistic linkage function has a flexible structure to accommodate the size of the linkage of individual GDP growth rates, and it strengthens the dynamics.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139483720","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}

引用次数: 0

An initial investigation for employing ACH depth function in degradation model selection: A case study with real data 在退化模型选择中使用 ACH 深度函数的初步研究：真实数据案例研究

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-14 DOI: 10.1002/asmb.2844

Arefe Asadi, Mitra Fouladirad, Diego Tomassi

引用次数: 0

Optimal maintenance policy for imperfect production systems using reliability function and defect rate 利用可靠性函数和缺陷率优化不完善生产系统的维护政策

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-04 DOI: 10.1002/asmb.2843

Jyh-Wen Ho, Yeu-Shiang Huang, Peng-Tsi Huang

引用次数: 0

Demand for live betting: An analysis using state-space models 现场投注需求：利用状态空间模型进行分析

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-04 DOI: 10.1002/asmb.2836

Marius Ötting, Rouven Michels, Roland Langrock, Christian Deutscher

引用次数: 0

Bayesian analysis of Markov modulated queues with abandonment 带放弃的马尔可夫调制队列的贝叶斯分析

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-04 DOI: 10.1002/asmb.2839

Atilla Ay, Joshua Landon, Süleyman Özekici, Refik Soyer

引用次数: 0

A dam management problem with energy production as an optimal switching problem 以能源生产为最佳转换问题的大坝管理问题

IF 1.4 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2023-12-29 DOI: 10.1002/asmb.2840

Etienne Chevalier, Cristina Di Girolami, M'hamed Gaïgi, Elisa Giovannini, Simone Scotti

引用次数: 0

Correction to deep reinforcement learning-based ordering mechanism for performance optimization in multi-echelon supply chains 修正基于深度强化学习的订购机制，以优化多供应链的性能

IF 1.3 4区数学

Applied Stochastic Models in Business and Industry Pub Date : 2023-12-28 DOI: 10.1002/asmb.2838

Dony S. Kurian, V. Madhusudanan Pillai

{"title":"Correction to deep reinforcement learning-based ordering mechanism for performance optimization in multi-echelon supply chains","authors":"Dony S. Kurian, V. Madhusudanan Pillai","doi":"10.1002/asmb.2838","DOIUrl":"10.1002/asmb.2838","url":null,"abstract":"<p>This paper addresses and acknowledges the valuable feedback provided by Dr. Deniz Preil in response to the recent study conducted by Kurian et al which investigates the application of proximal policy optimization (PPO) to determine dynamic ordering policies within multi-echelon supply chains. The first comment raised by Dr. Preil motivated an examination of the training and evaluation procedures in Experiments 2, 3, and 4. The Experiments 2 and 3 were reworked to address this, allowing the seed to vary for every training iteration, resulting in refined outcomes while there was no need of reworking of Experiment 4. The second comment focused on the benchmarking strategies involving the 1-1 policy and the order-up-to (OUT) policy, clarifying the distinctions between the two policies and justifying the use of the 1-1 policy for benchmarking in Experiment 4. The implementation of the widely accepted OUT policy was explained, highlighting the meaningful rationale behind its use. These discussions aim to enhance the methodology employed by Kurian et al and strengthen the implications of the findings within the domain of supply chain ordering management.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139062161","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}

引用次数: 0