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Censored autoregressive regression models with Student-t innovations 带有 Student-t 创新值的剔除自回归模型
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-02-21 DOI: 10.1002/cjs.11804
Katherine A. L. Valeriano, Fernanda L. Schumacher, Christian E. Galarza, Larissa A. Matos
{"title":"Censored autoregressive regression models with Student-t innovations","authors":"Katherine A. L. Valeriano,&nbsp;Fernanda L. Schumacher,&nbsp;Christian E. Galarza,&nbsp;Larissa A. Matos","doi":"10.1002/cjs.11804","DOIUrl":"10.1002/cjs.11804","url":null,"abstract":"<p>Data collected over time are common in applications and may contain censored or missing observations, making it difficult to use standard statistical procedures. This article proposes an algorithm to estimate the parameters of a censored linear regression model with errors serially correlated and innovations following a Student-<span></span><math>\u0000 <mrow>\u0000 <mi>t</mi>\u0000 </mrow></math> distribution. This distribution is widely used in the statistical modelling of data containing outliers because its longer-than-normal tails provide a robust approach to handling such data. The maximum likelihood estimates of the proposed model are obtained through a stochastic approximation of the EM algorithm. The methods are applied to an environmental dataset regarding ammonia-nitrogen concentration, which is subject to a limit of detection (left censoring) and contains missing observations. Additionally, two simulation studies are conducted to examine the asymptotic properties of the estimates and the robustness of the model. The proposed algorithm and methods are implemented in the R package <span>ARCensReg</span>.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11804","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055886","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}
引用次数: 0
Acknowledgement of referees' services remerciements aux membres des jurys 感谢推荐人提供的服务 remerciements aux membres des jurys
IF 0.6 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-02-15 DOI: 10.1002/cjs.11806
{"title":"Acknowledgement of referees' services remerciements aux membres des jurys","authors":"","doi":"10.1002/cjs.11806","DOIUrl":"https://doi.org/10.1002/cjs.11806","url":null,"abstract":"","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140123773","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
Semiparametric estimation for the functional additive hazards model 功能加性危害模型的半参数估计
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-01-11 DOI: 10.1002/cjs.11805
Meiling Hao, Kin-yat Liu, Wen Su, Xingqiu Zhao
{"title":"Semiparametric estimation for the functional additive hazards model","authors":"Meiling Hao,&nbsp;Kin-yat Liu,&nbsp;Wen Su,&nbsp;Xingqiu Zhao","doi":"10.1002/cjs.11805","DOIUrl":"10.1002/cjs.11805","url":null,"abstract":"<p>We propose a new functional additive hazards model to investigate the potential effects of functional and scalar predictors on mortality risks, and develop a penalized least squares estimation method for model parameters based on a pseudoscore estimating equation. A reproducing kernel Hilbert space approach is used to establish the consistency, convergence rate, and joint asymptotic distribution of the resulting estimators for finite-dimensional and infinite-dimensional parameters. Our simulation studies demonstrate that the proposed estimation procedure performs well. For illustration, we apply the proposed method to the Medical Information Mart for Intensive Care III dataset.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139421542","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
Clustering spatial functional data using a geographically weighted Dirichlet process 使用地理加权 Dirichlet 过程对空间功能数据进行聚类
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-01-05 DOI: 10.1002/cjs.11803
Tianyu Pan, Weining Shen, Guanyu Hu
{"title":"Clustering spatial functional data using a geographically weighted Dirichlet process","authors":"Tianyu Pan,&nbsp;Weining Shen,&nbsp;Guanyu Hu","doi":"10.1002/cjs.11803","DOIUrl":"10.1002/cjs.11803","url":null,"abstract":"<p>We propose a Bayesian nonparametric clustering approach to study the spatial heterogeneity effect for functional data observed at spatially correlated locations. We consider a geographically weighted Chinese restaurant process equipped with a conditional autoregressive prior to capture fully the spatial correlation of function curves. To sample efficiently from our model, we customize a prior called Quadratic Gamma, which ensures conjugacy. We design a Markov chain Monte Carlo algorithm to infer simultaneously the posterior distributions of the number of groups and the grouping configurations. The superior numerical performance of the proposed method over competing methods is demonstrated using simulated examples and a U.S. annual precipitation study.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055778","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 Model Selection via Composite Likelihood for High-dimensional Data Integration 通过复合似然进行贝叶斯模型选择，实现高维数据整合
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-01-05 DOI: 10.1002/cjs.11800
Guanlin Zhang, Yuehua Wu, Xin Gao
{"title":"Bayesian Model Selection via Composite Likelihood for High-dimensional Data Integration","authors":"Guanlin Zhang,&nbsp;Yuehua Wu,&nbsp;Xin Gao","doi":"10.1002/cjs.11800","DOIUrl":"10.1002/cjs.11800","url":null,"abstract":"<p>We consider data integration problems where correlated data are collected from multiple platforms. Within each platform, there are linear relationships between the responses and a collection of predictors. We extend the linear models to include random errors coming from a much wider family of sub-Gaussian and subexponential distributions. The goal is to select important predictors across multiple platforms, where the number of predictors and the number of observations both increase to infinity. We combine the marginal densities of the responses obtained from different platforms to form a composite likelihood and propose a model selection criterion based on Bayesian composite posterior probabilities. Under some regularity conditions, we prove that the model selection criterion is consistent to recover the union support of the predictors with divergent true model size.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140056288","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
Modelling occurrence and quantity of longitudinal semicontinuous data simultaneously with nonparametric unobserved heterogeneity 利用非参数非观测异质性同时对纵向半连续数据的发生和数量进行建模
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2023-12-09 DOI: 10.1002/cjs.11801
Guohua Yan, Renjun Ma
{"title":"Modelling occurrence and quantity of longitudinal semicontinuous data simultaneously with nonparametric unobserved heterogeneity","authors":"Guohua Yan,&nbsp;Renjun Ma","doi":"10.1002/cjs.11801","DOIUrl":"10.1002/cjs.11801","url":null,"abstract":"<p>Semicontinuous data frequently occur in longitudinal studies. The popular two-part modelling approach deals with longitudinal semicontinuous data by analyzing the occurrence of positive values and the intensity of positive values separately; however, this separation may break down the natural sequence of semicontinuous data within a subject and destroy its serial dependence structure. In this article, we introduce a Tweedie compound Poisson mixed model to study the occurrence of positive values and the quantity of the semicontinuous response simultaneously. In our approach, covariate effects on the semicontinuous response are assessed directly. The correlation within a subject and the unobserved heterogeneity are incorporated with serially correlated nonparametric random effects. Our model unifies subject-specific and population-averaged interpretations. We illustrate the approach with applications to a Brief Symptom Inventory study and an infants' fluoride intake study.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138561336","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 multiply robust imputation in the presence of influential units in surveys 在调查中有影响的单位存在的情况下，有效的乘法稳健估算
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2023-11-22 DOI: 10.1002/cjs.11802
Sixia Chen, David Haziza, Victoire Michal
{"title":"Efficient multiply robust imputation in the presence of influential units in surveys","authors":"Sixia Chen,&nbsp;David Haziza,&nbsp;Victoire Michal","doi":"10.1002/cjs.11802","DOIUrl":"10.1002/cjs.11802","url":null,"abstract":"<p>Item nonresponse is a common issue in surveys. Because unadjusted estimators may be biased in the presence of nonresponse, it is common practice to impute the missing values with the objective of reducing the nonresponse bias as much as possible. However, commonly used imputation procedures may lead to unstable estimators of population totals/means when influential units are present in the set of respondents. In this article, we consider the class of multiply robust imputation procedures that provide some protection against the failure of underlying model assumptions. We develop an efficient version of multiply robust estimators based on the concept of conditional bias, a measure of influence. We present the results of a simulation study to show the benefits of our proposed method in terms of bias and efficiency.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11802","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544108","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}
引用次数: 0
Football group draw probabilities and corrections 足球小组抽签概率和修正
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2023-11-10 DOI: 10.1002/cjs.11798
Gareth O. Roberts, Jeffrey S. Rosenthal
{"title":"Football group draw probabilities and corrections","authors":"Gareth O. Roberts,&nbsp;Jeffrey S. Rosenthal","doi":"10.1002/cjs.11798","DOIUrl":"10.1002/cjs.11798","url":null,"abstract":"<p>This article considers the challenge of designing football group draw mechanisms, which have a uniform distribution over all valid draw assignments, but are also entertaining, practical and transparent. Although this problem is trivial in completely symmetric problems, it becomes challenging when there are draw constraints that are not exchangeable across each of the competing teams, so that symmetry breaks down. We explain how to simulate the FIFA sequential draw method and compute the nonuniformity of its draws by comparison with a uniform rejection sampler. We then propose several practical methods of achieving the uniform distribution while still using balls and bowls in a way which is suitable for a televised draw. The solutions can also be carried out interactively. The general methodology we provide can readily be transported to different competition draws and is not restricted to football events.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135141646","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
Nonparametric estimation of a survival function in the presence of measurement errors on the failure time of interest 在相关故障时间存在测量误差的情况下，对生存函数进行非参数估计
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2023-11-10 DOI: 10.1002/cjs.11799
Shaojia Jin, Yanyan Liu, Guangcai Mao, Jianguo Sun, Yuanshan Wu
{"title":"Nonparametric estimation of a survival function in the presence of measurement errors on the failure time of interest","authors":"Shaojia Jin,&nbsp;Yanyan Liu,&nbsp;Guangcai Mao,&nbsp;Jianguo Sun,&nbsp;Yuanshan Wu","doi":"10.1002/cjs.11799","DOIUrl":"10.1002/cjs.11799","url":null,"abstract":"<p>This article discusses nonparametric estimation of a survival function in the presence of measurement errors on the observation of the failure time of interest. One situation where such issues arise would be clinical studies of chronic diseases where the observation on the time to the failure event of interest such as the onset of the disease relies on patient recall or chart review of electronic medical records. It is easy to see that both situations can be subject to measurement errors. To resolve this problem, we propose a simulation extrapolation approach to correct the bias induced by the measurement error. To overcome potential computational difficulties, we use spline regression to approximate the unspecified extrapolated coefficient function of time, and establish the asymptotic properties of our proposed estimator. The proposed method is applied to nonparametric estimation based on interval-censored data. Extensive numerical experiments involving both simulated and actual study datasets demonstrate the feasibility of this proposed estimation procedure.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135141149","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
Fused mean structure learning in data integration with dependence 具有依赖性的数据整合中的融合均值结构学习
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2023-10-27 DOI: 10.1002/cjs.11797
Emily C. Hector
{"title":"Fused mean structure learning in data integration with dependence","authors":"Emily C. Hector","doi":"10.1002/cjs.11797","DOIUrl":"10.1002/cjs.11797","url":null,"abstract":"<p>Motivated by image-on-scalar regression with data aggregated across multiple sites, we consider a setting in which multiple independent studies each collect multiple dependent vector outcomes, with potential mean model parameter homogeneity between studies and outcome vectors. To determine the validity of a joint analysis of these data sources, we must learn which of them share mean model parameters. We propose a new model fusion approach that delivers improved flexibility and statistical performance over existing methods. Our proposed approach specifies a quadratic inference function within each data source and fuses mean model parameter vectors in their entirety based on a new formulation of a pairwise fusion penalty. We establish theoretical properties of our estimator and propose an asymptotically equivalent weighted oracle meta-estimator that is more computationally efficient. Simulations and an application to the ABIDE neuroimaging consortium highlight the flexibility of the proposed approach. An <span>R</span> package is provided for ease of implementation.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136317032","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}
引用次数: 0
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