Econometrics and Statistics最新文献_第4页

Directional Tests and Confidence Bounds on Economic Inequality 经济不平等的方向检验和置信限

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.02.003

Jean-Marie Dufour , Emmanuel Flachaire , Lynda Khalaf , Abdallah Zalghout

引用次数: 0

Quasi Maximum Likelihood Estimation of Value at Risk and Expected Shortfall 风险价值与预期缺口的拟极大似然估计

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.08.003

Leopoldo Catania , Alessandra Luati

引用次数: 0

The dynamics of U.S. industrial production: A time-varying Granger causality perspective 美国工业生产的动态:一个时变格兰杰因果关系的观点

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.10.012

Christopher F. Baum , Stan Hurn , Jesús Otero

引用次数: 0

Threshold Autoregressive Nearest-Neighbour Models for Claims Reserving 索赔保留的阈值自回归近邻模型

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.03.006

Tak Kuen Siu

引用次数: 0

ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control ICS用于多变量功能异常检测，并应用于预测性维护和质量控制

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2022.03.003

Aurore Archimbaud , Feriel Boulfani , Xavier Gendre , Klaus Nordhausen , Anne Ruiz-Gazen , Joni Virta

{"title":"ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control","authors":"Aurore Archimbaud , Feriel Boulfani , Xavier Gendre , Klaus Nordhausen , Anne Ruiz-Gazen , Joni Virta","doi":"10.1016/j.ecosta.2022.03.003","DOIUrl":"10.1016/j.ecosta.2022.03.003","url":null,"abstract":"<div><div><span>Multivariate functional anomaly detection has received a large amount of attention recently. Accounting both the time dimension and the correlations between variables is challenging due to the existence of different types of outliers and the dimension of the data. In the context of </span>predictive maintenance<span> and quality control<span>, data sets often contain a large number of functional variables. However, most of the existing methods focus on a small number of functional variables. Moreover, in fields that have high reliability standards, detecting a small number of potential multivariate functional outliers with as few false positives as possible is crucial. In such a context, the adaptation of the Invariant Coordinate Selection (ICS) method from the multivariate to the multivariate functional case is of particular interest. Two extensions of ICS are proposed: point-wise and global. For both methods, the choice of the relevant components together with outlier identification and interpretation are discussed. A comparison is made on a predictive maintenance example from the avionics field and a quality control example from the microelectronics field. It appears that in such a context, point-wise and global ICS with a small number of selected components can be recommended.</span></span></div></div>","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"33 ","pages":"Pages 282-303"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82405360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Erratum regarding missing Declaration of Competing Interest statements in previously published articles 关于先前发表的文章中缺少竞争利益声明的勘误表

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.02.004

引用次数: 0

Erratum regarding missing Declaration of Competing Interest statements in previously published articles 关于先前发表的文章中缺少竞争利益声明的勘误表

IF 2

Econometrics and Statistics Pub Date : 2025-01-01 DOI: 10.1016/j.ecosta.2021.02.003

引用次数: 0

Empirical best predictors under multivariate Fay-Herriot models and their numerical approximation 多变量费-赫里奥特模型下的经验最佳预测值及其数值近似值

IF 1.9

Econometrics and Statistics Pub Date : 2024-09-10 DOI: 10.1016/j.ecosta.2024.09.001

Jan Pablo Burgard, Joscha Krause, Domingo Morales, Anna-Lena Wölwer

引用次数: 0

Forecasting with Machine Learning methods and multiple large datasets[formula omitted] 使用机器学习方法和多个大型数据集进行预测[公式省略]

IF 1.9

Econometrics and Statistics Pub Date : 2024-09-06 DOI: 10.1016/j.ecosta.2024.08.003

Nikoleta Anesti, Eleni Kalamara, George Kapetanios

{"title":"Forecasting with Machine Learning methods and multiple large datasets[formula omitted]","authors":"Nikoleta Anesti, Eleni Kalamara, George Kapetanios","doi":"10.1016/j.ecosta.2024.08.003","DOIUrl":"https://doi.org/10.1016/j.ecosta.2024.08.003","url":null,"abstract":"The usefulness of machine learning techniques for forecasting macroeconomic variables using multiple large datasets is considered. The predictive content of surveys is compared with text-based indicators from newspaper articles and a standard macroeconomic dataset, extending the evidence on the contribution of each dataset in predicting economic activity. Among the linear models, the Ridge regression and the Partial Least Squares models report the largest gains consistently for most of the forecasting horizons, and among the non linear machine learning models, Support Vector Regression performs better at shorter horizons compared to the Neural Networks and Random Forest that yield more accurate forecasts up to two years ahead. Text based indicators have similar informational content to surveys, albeit combining the two datasets provides with more accurate forecasts for most of the forecast horizons. The largest forecasting gains are overwhelmingly concentrated at the shorter horizons for the majority of models and datasets and they decrease significantly after one year. Non-linear machine learning models appear to be mostly useful during the Great Financial Crisis and perform similarly to their linear counterparts in more normal periods.","PeriodicalId":54125,"journal":{"name":"Econometrics and Statistics","volume":"27 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Specification tests for normal/gamma and stable/gamma stochastic frontier models based on empirical transforms 基于经验变换的正态/伽马和稳定/伽马随机前沿模型的规格检验

IF 1.9

Econometrics and Statistics Pub Date : 2024-08-28 DOI: 10.1016/j.ecosta.2024.08.002

Christos K. Papadimitriou, Simos G. Meintanis, Bernardo B. Andrade, Mike G. Tsionas

引用次数: 0