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KCBC – a correlation-based method for co-localization analysis of super-resolution microscopy images using bivariate Ripley's K functions KCBC - 一种基于相关性的方法，利用双变量里普利 K 函数对超分辨率显微镜图像进行共聚焦分析
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-29 DOI: 10.1080/02664763.2024.2346828
Xueyan Liu, Stephan Komladzei, Clifford Guy
{"title":"KCBC – a correlation-based method for co-localization analysis of super-resolution microscopy images using bivariate Ripley's K functions","authors":"Xueyan Liu, Stephan Komladzei, Clifford Guy","doi":"10.1080/02664763.2024.2346828","DOIUrl":"https://doi.org/10.1080/02664763.2024.2346828","url":null,"abstract":"Motivated by the high demand for co-localization analysis methods for super-resolution microscopy images which are featured with nanoscale precise locational information of molecules, this paper es...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"28 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141172344","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
On efficiency of locally D-optimal designs under heteroscedasticity and non-Gaussianity 论异方差和非高斯性条件下局部 D-最优设计的效率
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-29 DOI: 10.1080/02664763.2024.2346822
Xiao Zhang, Gang Shen
{"title":"On efficiency of locally D-optimal designs under heteroscedasticity and non-Gaussianity","authors":"Xiao Zhang, Gang Shen","doi":"10.1080/02664763.2024.2346822","DOIUrl":"https://doi.org/10.1080/02664763.2024.2346822","url":null,"abstract":"In the classical theory of locally optimal designs, which is developed within the framework of the center+error model, the most efficient design is the one based on MGLE, the maximum Gaussian likel...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"56 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141153163","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
A principal-weighted penalized regression model and its application in economic modeling 主加权惩罚回归模型及其在经济建模中的应用
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-26 DOI: 10.1080/02664763.2024.2346343
Mingwei Sun, Murong Xu
{"title":"A principal-weighted penalized regression model and its application in economic modeling","authors":"Mingwei Sun, Murong Xu","doi":"10.1080/02664763.2024.2346343","DOIUrl":"https://doi.org/10.1080/02664763.2024.2346343","url":null,"abstract":"This paper introduces a novel Principal-Weighted Penalized (PWP) regression model, designed for dimensionality reduction in large datasets without sacrificing essential information. This new model ...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"41 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141153168","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
Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification 基于尿液挥发性有机化合物 (VOC) 的前列腺癌诊断高维分类法
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-26 DOI: 10.1080/02664763.2024.2346355
George Ekow Quaye, Wen-Yee Lee, Elizabeth Noriega Landa, Sabur Badmos, Kiana L. Holbrook, Xiaogang Su
{"title":"Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification","authors":"George Ekow Quaye, Wen-Yee Lee, Elizabeth Noriega Landa, Sabur Badmos, Kiana L. Holbrook, Xiaogang Su","doi":"10.1080/02664763.2024.2346355","DOIUrl":"https://doi.org/10.1080/02664763.2024.2346355","url":null,"abstract":"Early detection of prostate cancer is critical for successful treatment and survival. However, current diagnostic methods such as prostate-specific antigen (PSA) testing and digital rectal examinat...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"20 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141511091","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
New results on optimal conditional error functions for adaptive two-stage designs 自适应两阶段设计的最佳条件误差函数新结果
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-17 DOI: 10.1080/02664763.2024.2342424
Maximilian Pilz, Meinhard Kieser
{"title":"New results on optimal conditional error functions for adaptive two-stage designs","authors":"Maximilian Pilz, Meinhard Kieser","doi":"10.1080/02664763.2024.2342424","DOIUrl":"https://doi.org/10.1080/02664763.2024.2342424","url":null,"abstract":"Unblinded interim analyses in clinical trials with adaptive designs are gaining increasing popularity. Here, the type I error rate is controlled by defining an appropriate conditional error functio...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"303 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612869","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
Bayesian extension of the Weibull AFT shared frailty model with generalized family of distributions for enhanced survival analysis using censored data 使用广义分布族对 Weibull AFT 共享虚弱模型进行贝叶斯扩展，以利用删失数据加强生存分析
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-11 DOI: 10.1080/02664763.2024.2338404
Mohammad Parvej, Athar Ali Khan
{"title":"Bayesian extension of the Weibull AFT shared frailty model with generalized family of distributions for enhanced survival analysis using censored data","authors":"Mohammad Parvej, Athar Ali Khan","doi":"10.1080/02664763.2024.2338404","DOIUrl":"https://doi.org/10.1080/02664763.2024.2338404","url":null,"abstract":"In survival analysis, the Accelerated Failure Time (AFT) shared frailty model is a widely used framework for analyzing time-to-event data while accounting for unobserved heterogeneity among individ...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"40 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570067","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
A combined superiority and non-inferiority procedure for comparing predictive values of two diagnostic tests 比较两种诊断测试预测值的优劣结合程序
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-04 DOI: 10.1080/02664763.2024.2335564
Kanae Takahashi, Kouji Yamamoto, Ayumi Shintani
{"title":"A combined superiority and non-inferiority procedure for comparing predictive values of two diagnostic tests","authors":"Kanae Takahashi, Kouji Yamamoto, Ayumi Shintani","doi":"10.1080/02664763.2024.2335564","DOIUrl":"https://doi.org/10.1080/02664763.2024.2335564","url":null,"abstract":"Positive and negative predictive values are useful to quantify the performance of medical tests, and both are often used simultaneously. Although there are several methods to test the equality of t...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"81 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570227","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
Matching a discrete distribution by Poisson matching quantiles estimation 通过泊松匹配量子估计匹配离散分布
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-04 DOI: 10.1080/02664763.2024.2337082
Hyungjun Lim, Arlene K. H. Kim
{"title":"Matching a discrete distribution by Poisson matching quantiles estimation","authors":"Hyungjun Lim, Arlene K. H. Kim","doi":"10.1080/02664763.2024.2337082","DOIUrl":"https://doi.org/10.1080/02664763.2024.2337082","url":null,"abstract":"Analyzing the data collected from different sources requires unpaired data analysis to account for the absence of correspondence between the random variable Y and the covariates X. Several attempts...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"57 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570397","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
Functional sufficient dimension reduction through information maximization with application to classification 通过信息最大化实现功能充分降维并应用于分类
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-03 DOI: 10.1080/02664763.2024.2335570
Xinyu Li, Jianjun Xu, Haoyang Cheng
{"title":"Functional sufficient dimension reduction through information maximization with application to classification","authors":"Xinyu Li, Jianjun Xu, Haoyang Cheng","doi":"10.1080/02664763.2024.2335570","DOIUrl":"https://doi.org/10.1080/02664763.2024.2335570","url":null,"abstract":"Considering the case where the response variable is a categorical variable and the predictor is a random function, two novel functional sufficient dimensional reduction (FSDR) methods are proposed ...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"60 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570265","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
Bayesian factor selection in a hybrid approach to confirmatory factor analysis 确认性因子分析混合方法中的贝叶斯因子选择
IF 1.5 4区 数学
Journal of Applied Statistics Pub Date : 2024-04-03 DOI: 10.1080/02664763.2024.2335568
Junyu Nie, Jihnhee Yu
{"title":"Bayesian factor selection in a hybrid approach to confirmatory factor analysis","authors":"Junyu Nie, Jihnhee Yu","doi":"10.1080/02664763.2024.2335568","DOIUrl":"https://doi.org/10.1080/02664763.2024.2335568","url":null,"abstract":"To investigate latent structures of measured variables, various factor structures are used for confirmatory factor analysis, including higher-order models and more flexible bifactor models. In prac...","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"22 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140570266","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
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