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Conditional empirical copula processes and generalized measures of association 条件经验copula过程与广义关联测度
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2075
A. Derumigny, J. Fermanian
{"title":"Conditional empirical copula processes and generalized measures of association","authors":"A. Derumigny, J. Fermanian","doi":"10.1214/22-ejs2075","DOIUrl":"https://doi.org/10.1214/22-ejs2075","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45621509","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
Sufficient dimension reduction for survival data analysis with error-prone variables 对易出错变量的生存数据分析进行足够的降维
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs1977
Li‐Pang Chen, G. Yi
{"title":"Sufficient dimension reduction for survival data analysis with error-prone variables","authors":"Li‐Pang Chen, G. Yi","doi":"10.1214/22-ejs1977","DOIUrl":"https://doi.org/10.1214/22-ejs1977","url":null,"abstract":": Sufficient dimension reduction (SDR) is an important tool in regression analysis which reduces the dimension of covariates without losing predictive information. Several methods have been proposed to handle data with either censoring in the response or measurement error in covariates. However, little research is available to deal with data having these two features simultaneously. In this paper, we examine this problem. We start with considering the cumulative distribution function in regular settings and propose a valid SDR method to incorporate the effects of censored data and covariates measurement error. Theoretical results are established, and numerical studies are reported to assess the performance of the proposed methods.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43949116","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: 2
Determine the number of clusters by data augmentation 通过数据扩充确定集群的数量
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2032
Wei Luo
{"title":"Determine the number of clusters by data augmentation","authors":"Wei Luo","doi":"10.1214/22-ejs2032","DOIUrl":"https://doi.org/10.1214/22-ejs2032","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43358941","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: 1
Augmented direct learning for conditional average treatment effect estimation with double robustness 双鲁棒条件平均处理效果估计的增强直接学习
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2025
Haomiao Meng, Xingye Qiao
{"title":"Augmented direct learning for conditional average treatment effect estimation with double robustness","authors":"Haomiao Meng, Xingye Qiao","doi":"10.1214/22-ejs2025","DOIUrl":"https://doi.org/10.1214/22-ejs2025","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46400127","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: 1
De-noising analysis of noisy data under mixed graphical models 混合图形模型下噪声数据的去噪分析
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2028
Li‐Pang Chen, G. Yi
{"title":"De-noising analysis of noisy data under mixed graphical models","authors":"Li‐Pang Chen, G. Yi","doi":"10.1214/22-ejs2028","DOIUrl":"https://doi.org/10.1214/22-ejs2028","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46756070","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
Robust sieve M-estimation with an application to dimensionality reduction 鲁棒筛m估计及其在降维中的应用
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2038
J. Bodelet, D. La Vecchia
{"title":"Robust sieve M-estimation with an application to dimensionality reduction","authors":"J. Bodelet, D. La Vecchia","doi":"10.1214/22-ejs2038","DOIUrl":"https://doi.org/10.1214/22-ejs2038","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66088450","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
Robust deep neural network estimation for multi-dimensional functional data 多维函数数据的鲁棒深度神经网络估计
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2093
Shuoyang Wang, Guanqun Cao
{"title":"Robust deep neural network estimation for multi-dimensional functional data","authors":"Shuoyang Wang, Guanqun Cao","doi":"10.1214/22-ejs2093","DOIUrl":"https://doi.org/10.1214/22-ejs2093","url":null,"abstract":": In this paper, we propose a robust estimator for the location function from multi-dimensional functional data. The proposed estimators are based on the deep neural networks with ReLU activation function. At the meanwhile, the estimators are less susceptible to outlying observations and model-misspecification. For any multi-dimensional functional data, we provide the uniform convergence rates for the proposed robust deep neural networks estimators. Simulation studies illustrate the competitive performance of the robust deep neural network estimators on regular data and their superior performance on data that contain anomalies. The proposed method is also applied to analyze 2D and 3D images of patients with Alzheimer’s disease obtained from the Alzheimer Disease Neuroimaging Initiative database.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41537501","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: 1
Depth level set estimation and associated risk measures 深度水平集估计和相关的风险措施
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs2095
Sara Armaut, Roland Diel, T. Laloë
{"title":"Depth level set estimation and associated risk measures","authors":"Sara Armaut, Roland Diel, T. Laloë","doi":"10.1214/22-ejs2095","DOIUrl":"https://doi.org/10.1214/22-ejs2095","url":null,"abstract":"","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42920277","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
Efficient nonparametric estimation of distribution for current status censoring 当前状态截尾下分布的有效非参数估计
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-ejs1980
S. Efromovich
{"title":"Efficient nonparametric estimation of distribution for current status censoring","authors":"S. Efromovich","doi":"10.1214/22-ejs1980","DOIUrl":"https://doi.org/10.1214/22-ejs1980","url":null,"abstract":"Abstract: Current status censoring (CSC) implies that there is no direct access to the lifetime of an event of interest. Instead it is known if the event already occurred or not at a random monitoring time. CSC is a simple sampling procedure and in many cases the only possibility to assess the lifetime of interest. At the same time, the absence of a direct measurement of a lifetime of interest makes the problem of nonparametric distribution estimation ill-posed. A simple, adaptive and sharp minimax estimator of the density and cumulative distribution function is proposed. The simplicity of estimator also allows us to relax assumptions. Practical examples illustrate CSC problem and the proposed estimator.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45616109","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
Measurability of functionals and of ideal point forecasts 函数和理想点预测的可测量性
IF 1.1 4区 数学
Electronic Journal of Statistics Pub Date : 2022-01-01 DOI: 10.1214/22-EJS2062
Tobias Fissler, H. Holzmann
{"title":"Measurability of functionals and of ideal point forecasts","authors":"Tobias Fissler, H. Holzmann","doi":"10.1214/22-EJS2062","DOIUrl":"https://doi.org/10.1214/22-EJS2062","url":null,"abstract":". The ideal probabilistic forecast for a random variable Y based on an information set F is the conditional distribution of Y given F . In the context of point forecasts aiming to specify a functional T such as the mean, a quantile or a risk measure, the ideal point forecast is the respective functional applied to the conditional distribution. This paper provides a theoretical justification why this ideal forecast is actually a forecast, that is, an F -measurable random variable. To that end, the appropriate notion of measurability of T is clarified and this measurability is established for a large class of practically relevant functionals, including elicitable ones. More generally, the measurability of T implies the measurability of any point forecast which arises by applying T to a probabilistic forecast. Similar measurability results are established for proper scoring rules, the main tool to evaluate the predictive accuracy of probabilistic forecasts.","PeriodicalId":49272,"journal":{"name":"Electronic Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43792730","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: 4
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