Journal of Applied Statistics最新文献

{"title":"<i>APCanalysis</i>: an <i>R</i> package for identifying active factors using the APC method.","authors":"Abu Zar Md Shafiullah, Arden Miller","doi":"10.1080/02664763.2025.2540378","DOIUrl":"10.1080/02664763.2025.2540378","url":null,"abstract":"<p><p>Unreplicated two-level designs play an important role in screening experiments. Notably, Plackett-Burman designs (PBDs) and regular fractional factorial designs ( <math><msup><mn>2</mn> <mrow><mi>k</mi> <mo>-</mo> <mi>p</mi></mrow> </msup> </math> ) are commonly used for their flexible run sizes and orthogonal contrasts. However, classical methods such as <i>t</i>-tests are not applicable for identifying significant effects in saturated models due to insufficient degrees of freedom. The All Possible Comparisons (APC) method addresses this limitation by providing an objective framework to control false positive rates, specifically the individual error rate (IER) and the experiment-wise error rate (EER). In this article, we introduce APCanalysis, a user-friendly R package that implements the APC method using a tailored AIC-type model selection criterion, the APC-criterion. The package features an advanced penalty algorithm extending error control to the false discovery rate (FDR). It supports main effects screening in PBDs, active main effects and interactions in full factorial ( <math><msup><mn>2</mn> <mi>k</mi></msup> </math> ) and resolution-V ( <math><msubsup><mn>2</mn> <mi>V</mi> <mrow><mi>k</mi> <mo>-</mo> <mi>p</mi></mrow> </msubsup> </math> ) designs, and detects active alias strings in resolution-IV ( <math><msubsup><mn>2</mn> <mrow><mi>IV</mi></mrow> <mrow><mi>k</mi> <mo>-</mo> <mi>p</mi></mrow> </msubsup> </math> ) and resolution-III ( <math><msubsup><mn>2</mn> <mrow><mi>III</mi></mrow> <mrow><mi>k</mi> <mo>-</mo> <mi>p</mi></mrow> </msubsup> </math> ) designs. Through examples, simulations, and real-world data, we demonstrate that the APC-criterion reliably identifies active factors while maintaining user-specified error thresholds for IER, EER, or FDR. Benchmarking against Lenth's method in a validation study further confirms strong agreement in screening power and accuracy. This article provides practical guidance on applying APCanalysis, highlighting its advantages and limitations. The package is available via the Comprehensive R Archive Network (CRAN).</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 5","pages":"937-957"},"PeriodicalIF":1.1,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13047717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147623023","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":"Extreme value theory for individuals control charts: a semiparametric approach to ensuring in-control performance.","authors":"Hong-Ji Yang, Chung-I Li","doi":"10.1080/02664763.2025.2554805","DOIUrl":"10.1080/02664763.2025.2554805","url":null,"abstract":"<p><p>This study introduces a semiparametric method for designing individuals control charts in Phase I statistical process monitoring, aimed at ensuring guaranteed in-control performance. Motivated by the limitations of parametric and nonparametric methods under small to moderate sample sizes, the proposed approach combines extreme value theory with the exceedance probability criterion to construct control limits that adjust for estimation variability. The methodology uses Pickands and moment estimators to model extreme tail behavior, offering a more reliable solution than purely data-driven nonparametric methods. Simulation results show that a sample size of approximately <math><mi>n</mi> <mo>=</mo> <mn>1112</mn></math> is sufficient to achieve a nominal coverage probability of <math><msub><mi>P</mi> <mrow><mrow><mi>n</mi></mrow> </mrow> </msub> <mo>=</mo> <mn>0.90</mn></math> . The method demonstrates strong and consistent performance across a variety of distributions, avoids the need for computationally intensive bootstrap procedures, and provides an R package for implementation to support reproducibility and real-world applications, such as semiconductor manufacturing.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 7","pages":"1181-1200"},"PeriodicalIF":1.1,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13228180/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156717","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":"Energy statistic-based modified information criterion for detecting the change in distribution.","authors":"Joseph Njuki, Wei Ning","doi":"10.1080/02664763.2025.2555606","DOIUrl":"10.1080/02664763.2025.2555606","url":null,"abstract":"<p><p>In this article, a test to detect the change in the distribution of sequence of independent random variables is proposed. To achieve this, we exploit the relationship between properties of U-statistics and Energy statistics (forms of V-statistics) to come up with a nonparametric test based on modified information criterion (MIC) in the change point detection using Energy statistics (EMIC). To investigate the performance of our proposed (EMIC) method, we assess the finite sample properties and compare efficiencies and powers of different methods with those of our method through simulations. Both the test procedure and the estimator of the location of the change point are consistent under the alternative hypothesis. In addition, simulation studies suggest that the proposed (EMIC) method is superior to other methods especially when the change occurs around the middle of the sequence. We then discuss its applications in two different real-life examples for detecting change in mean and variance.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 7","pages":"1274-1296"},"PeriodicalIF":1.1,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13228185/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156727","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":"Comparison of predictive values with paired samples.","authors":"Antonio Martín Andrés, Pedro Femia Marzo","doi":"10.1080/02664763.2025.2554824","DOIUrl":"10.1080/02664763.2025.2554824","url":null,"abstract":"<p><p>Positive predictive value and negative predictive value are two widely used parameters to assess the clinical usefulness of a medical diagnostic test. When there are two diagnostic tests, it is recommendable to make a comparative assessment of the values of these two parameters after applying the two tests to the same subjects (paired samples). The objective is then to make individual or global inferences about the difference or the ratio of the predictive value of the two diagnostic tests. We define the two properties of symmetry which any inference method must verify, we propose new inference methods, and we define them with simple expressions. All of the methods are compared with each other, concluding that the optimal method is: (1) in the case of a confidence interval for the difference or ratio, respectively, the classic method of Wang <i>et al.</i> and the new method that is proposed, both methods applied to the original data increased by 0.5; (2) in the case of individual homogeneity test of the two predictive values, the new method with the predictive values estimated subject to the null hypothesis; (3) in the case of a global homogeneity test of the two predictive values, the new method.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 7","pages":"1214-1236"},"PeriodicalIF":1.1,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13234884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148199101","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":"Developing optimal group acceptance sampling plans based on Weibull distribution with limited risks.","authors":"M Naghizadeh Qomi, Muhammad Aslam","doi":"10.1080/02664763.2025.2555591","DOIUrl":"10.1080/02664763.2025.2555591","url":null,"abstract":"<p><p>Single and group sampling plans are conventional methods for assessing the quality of submitted lots of products. The group scheme is considered as more efficient than the single sampling plan with respect to cost and time to reach the final decision about the submitted lot. In this paper, a group sampling plan for the lot acceptance is developed for the time-truncated life test when the lifetime of a product follows the Weibull distribution. The test plans are constructed by minimizing and limiting a weighted-average of the producer and consumer risks. Integer nonlinear programing is used to determine the optimal number of groups and the acceptance number. Several tables and figures are constructed to analyze the behavior of the proposed test plans. A comparison of the suggested <i>GASP</i> and the traditional optimal two-point plan shows that the proposed optimal plans outperform the optimal two-point plan in terms of sample size. A real data analysis is presented for illustration of the results. The results derived for Weibull distribution are also valid for any other lifetime model.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 7","pages":"1237-1252"},"PeriodicalIF":1.1,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13228191/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156700","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":"A note on two novel easy-to-interpret feature effect measures for partial dependence plots in a classification setting.","authors":"Andreas Karlsson Rosenblad","doi":"10.1080/02664763.2025.2554823","DOIUrl":"10.1080/02664763.2025.2554823","url":null,"abstract":"<p><p>Classification of observations into one of several distinct categories is a common task in applied statistics, traditionally performed using parametric statistical models such as logistic regression. These parametric models are, however, often outperformed in terms of prediction accuracy by black box supervised learning models (BBSLMs). A drawback of BBSLMs is the lack of easy-to-interpret feature effect measures similar to the odds ratio (OR) for logistic regression models. The present paper derives two novel feature effect measures based on partial dependence plots for binary classification using BBSLMs: the relative risk of marginal effects (RRME) and the odds ratio of marginal effects (ORME). The performance and interpretation of these new measures are illustrated in an application studying the risk of death within 48 hours of admission among individuals admitted to hospital with a myocardial infarction. The BBSLMs are shown to have better predictive ability than the logistic regression models, with the RRME:s and ORME:s of death for the main risk factor anterior infarct both being 1.8, comparable to the OR of 1.9 for the logistic regression model. The RRMEs and ORMEs are also shown to be more robust in terms of being applicable also for observations with missing values for some features.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 7","pages":"1201-1213"},"PeriodicalIF":1.1,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13228173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156600","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 analysis on single server Markovian queueing model with impatient customers.","authors":"Gulab Singh Bura, Himanshi Sharma","doi":"10.1080/02664763.2025.2552722","DOIUrl":"10.1080/02664763.2025.2552722","url":null,"abstract":"<p><p>This paper focuses on Bayesian inference of an M/M/1 queuing model with balking, a phenomenon in which customers choose not to join a queue due to long waiting line. In this paper, the balking probability is considered as a function of number of customers and their impatience level. The degree of impatience of customers plays a crucial role effecting the balking probability. Higher threshold of impatience implies that customers are more sensitive to queue length, i.e. they are less willing to join a queue when the queue is even slightly longer. Conversely, lower threshold of impatience indicates that customers will less balk. In this scenario, there is a higher probability that customers will opt to join the queue, even when it extends to a considerable length. This paper provides the Bayesian estimates for traffic intensity (<i>ρ</i>), employing various prior distributions such as beta, truncated gamma, and uniform prior distributions under a squared error loss function. Through the sampling importance re-sampling (SIR) technique, we obtained the posterior estimates, risk, and credible intervals that showcase the effectiveness of our methodology. Furthermore, simulation studies demonstrate the convergence of estimators, and our findings are further validated through analysis of real-life data.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 6","pages":"1098-1129"},"PeriodicalIF":1.1,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147815605","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":"Optimal ridge estimation in the restricted logistic semiparametric regression models using generalized cross-validation.","authors":"Mahdi Roozbeh","doi":"10.1080/02664763.2025.2541252","DOIUrl":"10.1080/02664763.2025.2541252","url":null,"abstract":"<p><p>Binary logistic semiparametric regression analysis is a commonly used statistical technique when the dependent variable is dichotomous or binary. In this analysis, the relationship between the success probability and certain explanatory variables is assumed to have a linear form, while the relationship to other variables is unknown. Multicollinearity is a serious problem that arises when explanatory variables in logistic semiparametric regression are highly correlated. It is well known that the variance of the maximum likelihood estimator is inflated due to multicollinearity in the semiparametric logistic regression model. Therefore, a novel stochastic restricted iterative weighted ridge estimator for logistic semiparametric regression is introduced, and its statistical properties are extracted asymptotically. Moreover, an extension of the generalized cross validation (GCV) function is introduced and applied for choosing the best values of the ridge parameter and the bandwidth of the kernel smoother. Additionally, some theorems are developed to illustrate the convergence of the GCV mean. Ultimately, the Monte-Carlo simulation studies and an actual real-life data set are conducted to support our theoretical discussion, and the findings indicated that the new estimator outperformed the other estimators under consideration.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 5","pages":"874-893"},"PeriodicalIF":1.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13045183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147623074","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":"On the robustness of truncated negative binomial regression model: application to field epidemiology.","authors":"Jiwoong Yu, Chanhee Kim, Jaeseong Oh, An-Shun Tai, Woojoo Lee","doi":"10.1080/02664763.2025.2545890","DOIUrl":"10.1080/02664763.2025.2545890","url":null,"abstract":"<p><p>Truncated count data are often obtained from field investigations conducted for individuals with some health-related symptoms to discover the possible causes of food-borne outbreaks quickly and accurately. This study shows two robust properties of the truncated negative binomial (TNB) model. First, by characterizing the whole set of models leading to the same likelihood function as the TNB model, we find a practical meaning that the TNB model gives reliable inference for the regression coefficients even zero inflation is allowed, but a careful interpretation of the regression coefficients is needed. Second, the TNB model can be derived from the Poisson distribution with the random intercept following a gamma distribution, however, it is difficult to justify the distribution assumption for the random intercept. We find that the TNB model presents robust inference for the slope parameters against a misspecified random effect distribution. With some analytic justifications, our numerical study shows that the empirical coverage based on the TNB model is close to its nominal level, even when the random effect distribution is misspecified. The TNB model is applied to analyze truncated count data from the food-borne outbreak that occurred in South Korea.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 6","pages":"1056-1074"},"PeriodicalIF":1.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147815590","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":"Change-point analysis using two-sample empirical likelihood method with applications to climatology.","authors":"Svetlana Aniskevich, Reinis Alksnis, Janis Valeinis, Lidija Dame","doi":"10.1080/02664763.2025.2543051","DOIUrl":"10.1080/02664763.2025.2543051","url":null,"abstract":"<p><p>The change-point detection in time series analysis is the problem of discovering time points at which the properties of data change. In this paper, we deal with detecting shifts in mean values for weakly dependent data. This covers a broad range of real-world problems since the real data may have a dependence structure that violates the assumptions of some popular statistical tests. For the change-point detection, we establish and propose to use the two-sample blockwise empirical likelihood for the difference of two-sample means. We recommend to produce the adjusted <i>p</i>-value graphs showing not only the statistical significance, but allowing also to detect the location of the change-point graphically and numerically. We compare the two-sample empirical likelihood method by the simulation study with some classical methods for the change-point detection and show the advantages of the method for weakly dependent observations. Using the historical wind speed observations in Latvia, we demonstrate the applicability of the proposed method to the real data. The method has been implemented using the R-package <i>EL</i>, which deals with different two-sample problems.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"53 6","pages":"1029-1055"},"PeriodicalIF":1.1,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147815596","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}