{"title":"gofCopula: Goodness-of-Fit Tests for Copulae","authors":"Ostap Okhrin, Simon Trimborn, Martin Waltz","doi":"10.2139/ssrn.3560825","DOIUrl":"https://doi.org/10.2139/ssrn.3560825","url":null,"abstract":"Last decades show an increased interest in modeling various types of data through copulae. Different copula models have been developed, which lead to the challenge of finding the best fitting model for a particular dataset. From the other side, a strand of literature developed a list of different Goodness-of-Fit (GoF) tests with different powers under different conditions. Usual practice is the selection of the best copula via the p-value of the GoF test. Although this method is not purely correct due to the fact that non-rejection does not imply acception, this strategy is favoured by practitioners. Unfortunately, different GoF tests often provide contradicting outputs. The proposed \u0000R-package brings under one umbrella 13 most used copulae - plus their rotated variants - together with 16 GoF tests and a hybrid one. The package offers flexible margin modeling, automatized parallelization, parameter estimation as well as a user friendly interface and pleasant visualizations of the results. To illustrate the functionality of the package, two exemplary applications are provided.","PeriodicalId":412850,"journal":{"name":"OPER: Information Technology (Topic)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116889450","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}
{"title":"Stability and Innovation in the Use of Forecasting Systems: A Case Study in a Supply-Chain Company","authors":"R. Fildes, P. Goodwin","doi":"10.2139/ssrn.3548701","DOIUrl":"https://doi.org/10.2139/ssrn.3548701","url":null,"abstract":"Computer-based demand forecasting systems have been widely adopted in supply chain companies, but little research has studied how these systems are actually used in the forecasting process. We report the findings of a case study of demand forecasting in a pharmaceutical company over a fifteen-year period. At the start of the study managers believed that they were making extensive use of their forecasting system that was marketed on the basis of the accuracy of its advanced statistical methods. Yet the majority of forecasts were obtained by using the system’s facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of an S & OP process, yet these often only served to reduce forecast accuracy. This study uses observations of the forecasting process, interviews with participants and data on the accuracy of forecasts to investigate the reasons underlying the managers’ use of the system at two levels, the individual and the organizational. This evidence is then interpreted using various theories to understand the longevity of the company’s forecasting process, despite potential economic benefits that could be achieved through change. However, 10 years after the original case observations radical transformations of the forecasting system were introduced. The paper concludes by considering the impetus for adopting the new system and processes, and the changes in organizational practices this has led to.","PeriodicalId":412850,"journal":{"name":"OPER: Information Technology (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121046126","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}
{"title":"Does the Multisecretary Problem Always Have Bounded Regret?","authors":"R. Bray","doi":"10.2139/ssrn.3497056","DOIUrl":"https://doi.org/10.2139/ssrn.3497056","url":null,"abstract":"Arlotto and Gurvich (2019) showed that the regret in the multisecretary problem is bounded in the number of job openings, n, and the number of applicants, k, provided that the applicant valuations are drawn from a distribution with finite support. I show that this result does not hold when applicant valuations are drawn from a standard uniform distribution. In this case, the regret is between log(n)/16 - 1/4 and log(n+1)/8, when k = n/2 and n ≥ 16. I establish these bounds with enhanced version of Vera and Banerjee's (2019) compensated coupling technique.","PeriodicalId":412850,"journal":{"name":"OPER: Information Technology (Topic)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122725057","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}