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Correction to “Matching distributions for survival data” 对“生存数据匹配分布”的更正
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-04-04 DOI: 10.1002/cjs.70007
{"title":"Correction to “Matching distributions for survival data”","authors":"","doi":"10.1002/cjs.70007","DOIUrl":"https://doi.org/10.1002/cjs.70007","url":null,"abstract":"<p>Jiang, Q., Xia, Y., and Liang, B. (2022) Matching distributions for survival data. <i>The Canadian Journal of Statistics</i>, 50:751–775.</p><p>The name of the first author “Qiang JIANG” was incorrect. This should have been: “Qing JIANG”.</p><p>We apologize for this error.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108866","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 对裁判服务的认可
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-02-26 DOI: 10.1002/cjs.11840
{"title":"Acknowledgement of Referees' Services Remerciements aux membres des jurys","authors":"","doi":"10.1002/cjs.11840","DOIUrl":"https://doi.org/10.1002/cjs.11840","url":null,"abstract":"","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497132","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 parameter transformation of the anisotropic Matérn covariance function 各向异性mat<s:1>协方差函数的参数变换
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-02-10 DOI: 10.1002/cjs.11839
Kamal Rai, Patrick E. Brown
{"title":"A parameter transformation of the anisotropic Matérn covariance function","authors":"Kamal Rai,&nbsp;Patrick E. Brown","doi":"10.1002/cjs.11839","DOIUrl":"https://doi.org/10.1002/cjs.11839","url":null,"abstract":"<p>We describe a polar coordinate transformation of the anisotropy parameters of the Matérn covariance function, which provides two benefits over the standard parameterization. First, it identifies a single point (the origin) with the special case of isotropy. Second, the posterior distribution of the transformed anisotropic angle and ratio is approximately bell-shaped and unimodal even in the case of isotropy. This has advantages for parameter inference and density estimation. We also apply a transformation to the standard deviation and range such that they are approximately orthogonal. We demonstrate this parameter transformation through two simulated and two real data sets, and conclude by considering possible extensions, such as implementing this transformation for approximate Bayesian inference methods.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108932","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
The quantile-based classifier with variable-wise parameters 具有可变参数的基于分位数的分类器
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-02-01 DOI: 10.1002/cjs.11837
Marco Berrettini, Christian Martin Hennig, Cinzia Viroli
{"title":"The quantile-based classifier with variable-wise parameters","authors":"Marco Berrettini,&nbsp;Christian Martin Hennig,&nbsp;Cinzia Viroli","doi":"10.1002/cjs.11837","DOIUrl":"https://doi.org/10.1002/cjs.11837","url":null,"abstract":"<p>Quantile-based classifiers can classify high-dimensional observations by minimizing a discrepancy of an observation to a class based on suitable quantiles of the within-class distributions, corresponding to a unique percentage for all variables. The present work extends these classifiers by introducing a way to determine potentially different optimal percentages for different variables. Furthermore, a variable-wise scale parameter is introduced. A simple greedy algorithm to estimate the parameters is proposed. Their consistency in a nonparametric setting is proved. Experiments using artificially generated and real data confirm the potential of the quantile-based classifier with variable-wise parameters.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11837","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108731","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
Balanced longitudinal data clustering with a copula kernel mixture model 基于copula核混合模型的平衡纵向数据聚类
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-01-31 DOI: 10.1002/cjs.11838
Xi Zhang, Orla A. Murphy, Paul D. McNicholas
{"title":"Balanced longitudinal data clustering with a copula kernel mixture model","authors":"Xi Zhang,&nbsp;Orla A. Murphy,&nbsp;Paul D. McNicholas","doi":"10.1002/cjs.11838","DOIUrl":"https://doi.org/10.1002/cjs.11838","url":null,"abstract":"<p>Many common clustering methods cannot be used for clustering balanced multivariate longitudinal data in cases where the covariance of variables is a function of the time points. In this article, a copula kernel mixture model (CKMM) is proposed for clustering data of this type. The CKMM is a finite mixture model that decomposes each mixture component's joint density function into a copula and marginal distribution functions. In this decomposition, the Gaussian copula is used due to its mathematical tractability and Gaussian kernel functions are used to estimate the marginal distributions. A generalized expectation-maximization algorithm is used to estimate the model parameters. The performance of the proposed model is assessed in a simulation study and on two real datasets. The proposed model is shown to have effective performance in comparison with standard methods, such as <span></span><math>\u0000 <mrow>\u0000 <mi>K</mi>\u0000 </mrow></math>-means with dynamic time warping clustering, latent growth models and functional high-dimensional data clustering.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11838","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497168","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
Susceptible-infected-recovered model with stochastic transmission 随机传播易感-感染-恢复模型
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2025-01-31 DOI: 10.1002/cjs.11835
Christian Gouriéroux, Yang Lu
{"title":"Susceptible-infected-recovered model with stochastic transmission","authors":"Christian Gouriéroux,&nbsp;Yang Lu","doi":"10.1002/cjs.11835","DOIUrl":"https://doi.org/10.1002/cjs.11835","url":null,"abstract":"<p>The susceptible-infected-recovered (SIR) model is the cornerstone of epidemiological models. However, this specification depends on two parameters only, which results in its lack of flexibility and explains its difficulty to replicate the volatile reproduction numbers observed in practice. We extend the standard SIR model to a semiparametric SIR model, by first introducing a functional parameter of transmission, and then making this function stochastic. This leads to a SIR model with stochastic transmission. Our model is particularly tractable. We derive its closed-form solution and use it to compute key indicators, such as the condition (and the threshold) of herd immunity and the timing of the peak. When the population size is finite and the observations are in discrete time, there is also observational uncertainty. We propose a nonlinear state-space framework under which we analyze the relative magnitudes of the observational and intrinsic uncertainties during the evolution of the epidemic. We emphasize the lack of robustness of the notion of herd immunity when the SIR model is time-discretized.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108973","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
Probabilistic weighted Dirichlet process mixture with an application to stochastic volatility models 概率加权狄利克雷混合过程及其在随机波动模型中的应用
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-12-31 DOI: 10.1002/cjs.11834
Peng Sun, Inyoung Kim, Ki-Ahm Lee
{"title":"Probabilistic weighted Dirichlet process mixture with an application to stochastic volatility models","authors":"Peng Sun,&nbsp;Inyoung Kim,&nbsp;Ki-Ahm Lee","doi":"10.1002/cjs.11834","DOIUrl":"https://doi.org/10.1002/cjs.11834","url":null,"abstract":"<p>In this article, we propose a flexible Bayesian modelling framework and investigate the probabilistic weighted Dirichlet process mixture (pWDPM). The construction and properties of a probabilistic weight function are illustrated. The advantage of the pWDPM under the log-squared transformed stochastic volatility (SV) model is demonstrated. We achieve greater modelling flexibility by relaxing the distributional assumption of the error term. Bayesian inference for the pWDPM under SV and sampling procedures are provided. The performance of the pWDPM is evaluated using simulation studies and empirical results. Both computational efficiency and model accuracy are achieved through the pWDPM.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11834","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108972","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
A new class of asymptotic maximin distance Latin hypercube designs 一类新的渐近极大距离拉丁超立方体设计
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-12-30 DOI: 10.1002/cjs.11836
Xinxin Xia, Wenlong Li, Pengnan Li
{"title":"A new class of asymptotic maximin distance Latin hypercube designs","authors":"Xinxin Xia,&nbsp;Wenlong Li,&nbsp;Pengnan Li","doi":"10.1002/cjs.11836","DOIUrl":"https://doi.org/10.1002/cjs.11836","url":null,"abstract":"<p>Maximin distance Latin hypercube designs have been widely used in computer experiments because they can achieve one-dimensional stratification and full-dimensional space-filling properties. In this article, we propose a new method for constructing a class of Latin hypercube designs that can accommodate many columns. We show that the resulting designs are asymptotically optimal under the maximin distance criterion, and enjoy a large proportion of low-dimensional stratification properties that strong orthogonal arrays should have. In addition, the proposed method can be used to construct a class of asymptotically optimal sliced maximin distance Latin hypercube designs. These designs are well suited to computer experiments due to their good space-filling properties.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108970","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
True and false discoveries with independent and sequential e-values 具有独立和连续电子值的真假发现
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-10-21 DOI: 10.1002/cjs.11833
Vladimir Vovk, Ruodu Wang
{"title":"True and false discoveries with independent and sequential e-values","authors":"Vladimir Vovk,&nbsp;Ruodu Wang","doi":"10.1002/cjs.11833","DOIUrl":"https://doi.org/10.1002/cjs.11833","url":null,"abstract":"<p>In this article, we use <i>e</i>-values in the context of multiple hypothesis testing, assuming that the base tests produce independent, or sequential, <i>e</i>-values. Our simulation and empirical studies, as well as theoretical considerations, suggest that, under this assumption, our new algorithms are superior to the known algorithms using independent <i>p</i>-values and to our recent algorithms designed for <i>e</i>-values without the assumption of independence.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"52 4","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11833","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642392","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
Robust causal inference for point exposures with missing confounders 缺失混杂因素的点暴露的稳健因果推理
IF 0.8 4区 数学
Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2024-09-19 DOI: 10.1002/cjs.11832
Alexander W. Levis, Rajarshi Mukherjee, Rui Wang, Sebastien Haneuse
{"title":"Robust causal inference for point exposures with missing confounders","authors":"Alexander W. Levis,&nbsp;Rajarshi Mukherjee,&nbsp;Rui Wang,&nbsp;Sebastien Haneuse","doi":"10.1002/cjs.11832","DOIUrl":"https://doi.org/10.1002/cjs.11832","url":null,"abstract":"<p>Large observational databases are often subject to missing data. As such, methods for causal inference must simultaneously handle confounding and missingness; surprisingly little work has been done at this intersection. Motivated by this, we propose an efficient and robust estimator of the causal average treatment effect from cohort studies when confounders are missing at random. The approach is based on a novel factorization of the likelihood that, unlike alternative methods, facilitates flexible modelling of nuisance functions (e.g., with state-of-the-art machine learning methods) while maintaining nominal convergence rates of the final estimators. Simulated data, derived from an electronic health record-based study of the long-term effects of bariatric surgery on weight outcomes, verify the robustness properties of the proposed estimators in finite samples. Our approach may serve as a theoretical benchmark against which ad hoc methods may be assessed.</p>","PeriodicalId":55281,"journal":{"name":"Canadian Journal of Statistics-Revue Canadienne De Statistique","volume":"53 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjs.11832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108979","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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