{"title":"A Note on the Beta Distribution of Lot Percent Defective","authors":"J. Chimka","doi":"10.1515/eqc-2015-0010","DOIUrl":"https://doi.org/10.1515/eqc-2015-0010","url":null,"abstract":"Abstract In this note I use MIL-STD-414 for contrast and comparison with an alternate way to estimate the distribution of lot percent defective. A slight deviation from traditional distribution assumption parameters affects results associated with an enduring example of double specification limits.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114626294","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":"On Valid Signals in Joint Schemes for the Process Mean and Variance","authors":"Tânia Ralha, M. Morais, M. R. Oliveira","doi":"10.1515/eqc-2015-0001","DOIUrl":"https://doi.org/10.1515/eqc-2015-0001","url":null,"abstract":"Abstract Joint schemes for the process mean and the variance are essential to determine if unusual variation in the location and spread of a quality characteristic occurred. This paper comprises a systematic study on the phenomena of misleading, unambiguous and simultaneous signals while dealing with Shewhart and EWMA joint schemes for the process mean and the variance of a normally distributed quality characteristic. Examples have been added to illustrate how the R statistical software can be used to assess the performance of joint schemes in practice, namely when it comes to the occurrence of those valid signals.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121398346","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}
S. Nayeban, A. Rezaei Roknabadi, G. M. Mohtashami Borzadaran
{"title":"Comparison of Lower Bounds for the Variance of Unbiased Estimators for some Well-known Families of Distributions","authors":"S. Nayeban, A. Rezaei Roknabadi, G. M. Mohtashami Borzadaran","doi":"10.1515/eqc-2013-0016","DOIUrl":"https://doi.org/10.1515/eqc-2013-0016","url":null,"abstract":"Abstract One of the most fundamental issues in estimation theory about accuracy of an unbiased estimator is computing or approximating its variance. Very often, the variance has a complicated form or cannot be computed explicitly. In this paper, we consider two well-known lower bounds for the variance of unbiased estimator, namely the Bhattacharyya (1946, 1947) and the Kshirsagar (2000) bounds for some versatile families of distributions in statistics and especially in reliability analysis. We consider the generalized gamma (GG), inverse Gaussian, Burr type XII and Burr type III distributions, and derive for these distributions, general forms of Bhattacharyya and Kshirsagar matrices. Additionally, we evaluate different Bhattacharyya and Kshirsagar bounds for the variance of estimators of some functions of relevant parameters and arrive at proposal which of the bounds should be used in given situations.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134317328","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":"Checking Default Correlation and Score Correlation in a Breakpoint Model for Rating Classification","authors":"Daniel Tillich","doi":"10.1515/eqc-2015-0006","DOIUrl":"https://doi.org/10.1515/eqc-2015-0006","url":null,"abstract":"Abstract In credit risk, debtors with different creditworthiness are divided into rating classes. One problem is to define the borders of the rating classes. A natural way to estimate these breakpoints from default observations comes out of the field of change point analysis. In order to account for dependency between the debtors, the literature proposes a combination of a breakpoint model with a one-factor model. One finds strongly consistent estimators for the threshold of the rating classes and the corresponding default probabilities, also called risk levels. But an investigation of the inherent model properties is as yet missing. For this reason we derive the default correlation and study its relationship to the model parameters, i.e., the breakpoint, the risk levels, and a new correlation term, named score correlation, appearing in a simulation study. Eventually, we check the magnitude of the score correlation used in the simulation study.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123149740","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":"Selection of modified quick switching systems for given acceptable and limiting quality levels with minimum risks using weighted poisson distribution","authors":"S. Kandasamy, Haridoss Venugopal","doi":"10.1515/EQC-2013-0021","DOIUrl":"https://doi.org/10.1515/EQC-2013-0021","url":null,"abstract":"Abstract Since the first acceptance sampling plans have been developed 80 years ago, a number of selection principles have emerged. The majority of these principles are characterized by the fact that they look upon producer and consumer as two opposing parties. However, in many occasions, e.g., in final inspection, producer and consumer represent the same party and, therefore, the used sampling plan should not make an attempt to discriminate between their interests. In this case the interest is to avoid wrong decisions, i.e., reject product of sufficient quality and accept product of insufficient quality. Thus, the natural objective in these cases is to use overall risk for a wrong decision as optimization criteria. In this paper, a table and procedure are given for finding the Modified Quick Switching Systems QSS − m(n;CN, CT) involving minimum sum of producer's and consumer's risks for specified Acceptable Quality Level and Limiting Quality Level using weighted Poisson distribution.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115875272","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":"Nonlinear Tobit Decomposition","authors":"Zhang Yi, Wang Yi, Nadarajah Saralees","doi":"10.1515/EQC.2006.271","DOIUrl":"https://doi.org/10.1515/EQC.2006.271","url":null,"abstract":"This paper extends the decomposition of marginal effects suggested by McDonald and Moffitt [The Review of Economics and Statistics 62: 318-321, 1980] to a nonlinear tobit model, considering the increasing use of tobit analysis and substantive economic implications of the decomposition. The decomposition provides more information than is commonly realized based on the coefficients obtained from fitting a tobit model. In this paper the generalized decomposition of marginal effects is derived and the effects in the decomposition are expressed in explicit and closed form. A simulation study illustrates the application of the nonlinear decomposition using a simple nonlinear consumption function, along with maximum likelihood estimation on the parameters of the nonlinear tobit regression model.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122734570","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":"Comparing Data Envelopment Analysis and Human Decision Making Unit Rankings: A Survey Approach","authors":"Stanko Dimitrov","doi":"10.1515/eqc-2014-0013","DOIUrl":"https://doi.org/10.1515/eqc-2014-0013","url":null,"abstract":"In this paperwe compare the ordinal rankings generated throughData Envelopment Analysis (DEA) methods to ordinal rankings generated by human decision makers. Through eliciting the total rank ordering for approximately 100 individuals on all of the four di erent datasets of Decision Making Units (DMUs), we compare the rankings generated by individuals to those generated by ten DEA methods. We observe that depending on the characteristics of the dataset one of the DEA methods performs better than the others in matching human decision makers.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125171109","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":"Economic Reliability Group Acceptance Sampling Plans Based on the Inverse-Rayleigh and the Log-Logistic Distributions","authors":"A. Muhammad, M. A. Razzaque","doi":"10.1515/EQC.2011.002","DOIUrl":"https://doi.org/10.1515/EQC.2011.002","url":null,"abstract":"Economic reliability group acceptance sampling plans are developed assuming that the lifetime of a submitted product follows the inverse-Rayleigh or log-logistic distribution. For various acceptance numbers, sample size and producer's risks, plans with minimum experimental time are obtained that are smaller than for conventional plans. The results are illustrated by tables and examples.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116041534","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":"Selection of Bayesian Single Sampling Plans by Attributes with Desired Discrimination","authors":"R. Vijayaraghavan, A. Loganathan, K. Rajagopal","doi":"10.1515/eqc-2013-0023","DOIUrl":"https://doi.org/10.1515/eqc-2013-0023","url":null,"abstract":"Abstract Acceptance sampling is one of the celebrated techniques in quality assurance. The application of acceptance sampling methodology has been widespread in the industrial environment and the concept is being used primarily for incoming or receiving inspection. It is concerned with inspection of one or more samples drawn randomly from a lot or lots of finished products or materials and with decision making regarding lots on the basis of the information contained in the sample(s) about the quality of the products. A sampling plan under acceptance sampling is a rule that precisely specifies the parameters of the sampling process and acceptance/rejection criteria and may be one of two categories, viz., attributes and variables. The theory of acceptance sampling plans by attributes is based on the implicit assumption that the production process from which lots are formed is stable and the lot or process fraction nonconforming is a constant. However, the lots formed from a process, in practice, have quality variations, which occur due to random fluctuations, and thereby the proportion of non-conforming units in the lots will vary continuously. Hence, in such cases, a framework of Bayesian methodology, which uses prior information on the process variation for making decisions about the submitted lots, can be employed as an alternative to conventional plans. Such plans are called Bayesian acceptance sampling plans. In this paper, Bayesian single sampling plans by attributes are developed under the conditions of Poisson distribution for sampling information and gamma distribution for prior process information. The methodology for determining the plan parameters based on unity values with operating ratio as a measure of discrimination is discussed. The procedures for the determination of an optimum plan and for the construction of operating characteristic curve are also presented. The Bayesian plans are compared with the plan under conventional method through an illustration.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115532979","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":"How We Can Evaluate the Inequality in Flint","authors":"F. Porro","doi":"10.1515/eqc-2014-0012","DOIUrl":"https://doi.org/10.1515/eqc-2014-0012","url":null,"abstract":"Abstract The inequality analysis plays an important role since the beginning of the last century, in the economic, social and political debate. From the first pioneering paper of Gini, this subject has become more and more fascinating. The several tools proposed in the literature for evaluating the inequality belong basically to two families: on the one hand there are inequality curves which represent (also graphically) the local pattern of inequality in all segments of the considered population; on the other hand, inequality indexes (that often can be derived from a particular inequality curve) which summarize its measure in one number. Different indexes are needed to reveal different viewpoints toward inequality. In this paper, the features of the relatively new inequality I(p) curve are described. Beyond many theoretical results, also an empirical analysis based on real income data of Flint is performed.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114878327","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}