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Scandinavian Journal of Statistics最新文献

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Divergence versus decision P‐values: A distinction worth making in theory and keeping in practice: Or, how divergence P‐values measure evidence even when decision P‐values do not 分歧与决策P值:一个值得在理论和实践中做出的区分;或者，分歧P值如何衡量证据，即使决策P值没有
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-12-11 DOI: 10.1111/sjos.12625
S. Greenland
{"title":"Divergence versus decision P‐values: A distinction worth making in theory and keeping in practice: Or, how divergence P‐values measure evidence even when decision P‐values do not","authors":"S. Greenland","doi":"10.1111/sjos.12625","DOIUrl":"https://doi.org/10.1111/sjos.12625","url":null,"abstract":"There are two distinct definitions of “P‐value” for evaluating a proposed hypothesis or model for the process generating an observed dataset. The original definition starts with a measure of the divergence of the dataset from what was expected under the model, such as a sum of squares or a deviance statistic. A P‐value is then the ordinal location of the measure in a reference distribution computed from the model and the data, and is treated as a unit‐scaled index of compatibility between the data and the model. In the other definition, a P‐value is a random variable on the unit interval whose realizations can be compared to a cutoff α to generate a decision rule with known error rates under the model and specific alternatives. It is commonly assumed that realizations of such decision P‐values always correspond to divergence P‐values. But this need not be so: Decision P‐values can violate intuitive single‐sample coherence criteria where divergence P‐values do not. It is thus argued that divergence and decision P‐values should be carefully distinguished in teaching, and that divergence P‐values are the relevant choice when the analysis goal is to summarize evidence rather than implement a decision rule.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"54 - 88"},"PeriodicalIF":1.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42293279","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: 6
Robust quasi‐randomization‐based estimation with ensemble learning for missing data 缺失数据的基于集成学习的稳健准随机化估计
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-12-11 DOI: 10.1111/sjos.12626
Danhyang Lee, Li‐Chun Zhang, Sixia Chen
{"title":"Robust quasi‐randomization‐based estimation with ensemble learning for missing data","authors":"Danhyang Lee, Li‐Chun Zhang, Sixia Chen","doi":"10.1111/sjos.12626","DOIUrl":"https://doi.org/10.1111/sjos.12626","url":null,"abstract":"Missing data analysis requires assumptions about an outcome model or a response probability model to adjust for potential bias due to nonresponse. Doubly robust (DR) estimators are consistent if at least one of the models is correctly specified. Multiply robust (MR) estimators extend DR estimators by allowing for multiple models for both the outcome and/or response probability models and are consistent if at least one of the multiple models is correctly specified. We propose a robust quasi‐randomization‐based model approach to bring more protection against model misspecification than the existing DR and MR estimators, where any multiple semiparametric, nonparametric or machine learning models can be used for the outcome variable. The proposed estimator achieves unbiasedness by using a subsampling Rao–Blackwell method, given cell‐homogenous response, regardless of any working models for the outcome. An unbiased variance estimation formula is proposed, which does not use any replicate jackknife or bootstrap methods. A simulation study shows that our proposed method outperforms the existing multiply robust estimators.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"1263 - 1278"},"PeriodicalIF":1.0,"publicationDate":"2022-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41355945","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
Selection of linear mixed‐effects models for clustered data 聚类数据线性混合效应模型的选择
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-12-08 DOI: 10.1111/sjos.12623
Chih‐Hao Chang, Hsin-Cheng Huang, C. Ing
{"title":"Selection of linear mixed‐effects models for clustered data","authors":"Chih‐Hao Chang, Hsin-Cheng Huang, C. Ing","doi":"10.1111/sjos.12623","DOIUrl":"https://doi.org/10.1111/sjos.12623","url":null,"abstract":"We consider model selection for linear mixed‐effects models with clustered structure, where conditional Kullback–Leibler (CKL) loss is applied to measure the efficiency of the selection. We estimate the CKL loss by substituting the empirical best linear unbiased predictors (EBLUPs) into random effects with model parameters estimated by maximum likelihood. Although the BLUP approach is commonly used in predicting random effects and future observations, selecting random effects to achieve asymptotic loss efficiency concerning CKL loss is challenging and has not been well studied. In this paper, we propose addressing this difficulty using a conditional generalized information criterion (CGIC) with two tuning parameters. We further consider a challenging but practically relevant situation where the number, m$$ m $$ , of clusters does not go to infinity with the sample size. Hence the random‐effects variances are not consistently estimable. We show that via a novel decomposition of the CKL risk, the CGIC achieves consistency and asymptotic loss efficiency, whether m$$ m $$ is fixed or increases to infinity with the sample size. We also conduct numerical experiments to illustrate the theoretical findings.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"875 - 897"},"PeriodicalIF":1.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44731261","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
The Kendall and Spearman rank correlations of the bivariate skew normal distribution 二元偏斜正态分布的Kendall和Spearman秩相关性
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-12-01 DOI: 10.1111/sjos.12587
Andréas Heinen, Alfonso Valdesogo
{"title":"The Kendall and Spearman rank correlations of the bivariate skew normal distribution","authors":"Andréas Heinen, Alfonso Valdesogo","doi":"10.1111/sjos.12587","DOIUrl":"https://doi.org/10.1111/sjos.12587","url":null,"abstract":"We derive the Kendall and Spearman rank correlation coefficients of the bivariate skew normal (SN) distribution. For a given correlation parameter, we provide conditions on the shape parameters, under which the SN is more dependent than the normal in terms of each of the two‐rank correlations. We further show how our results can be used for rank‐based estimation procedures of the correlation parameter and the equal shape parameter of the SN, whose consistency and asymptotic normality we establish.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"49 1","pages":"1669 - 1698"},"PeriodicalIF":1.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42608100","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
Issue Information 问题信息
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-11-16 DOI: 10.1111/sjos.12536
{"title":"Issue Information","authors":"","doi":"10.1111/sjos.12536","DOIUrl":"https://doi.org/10.1111/sjos.12536","url":null,"abstract":"","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":" ","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46923490","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
Distributed inference for two‐sample U‐statistics in massive data analysis 海量数据分析中两样本U统计量的分布式推断
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-10-06 DOI: 10.1111/sjos.12620
Bingyao Huang, Yanyan Liu, Liuhua Peng
{"title":"Distributed inference for two‐sample U‐statistics in massive data analysis","authors":"Bingyao Huang, Yanyan Liu, Liuhua Peng","doi":"10.1111/sjos.12620","DOIUrl":"https://doi.org/10.1111/sjos.12620","url":null,"abstract":"This paper considers distributed inference for two‐sample U‐statistics under the massive data setting. In order to reduce the computational complexity, this paper proposes distributed two‐sample U‐statistics and blockwise linear two‐sample U‐statistics. The blockwise linear two‐sample U‐statistic, which requires less communication cost, is more computationally efficient especially when the data are stored in different locations. The asymptotic properties of both types of distributed two‐sample U‐statistics are established. In addition, this paper proposes bootstrap algorithms to approximate the distributions of distributed two‐sample U‐statistics and blockwise linear two‐sample U‐statistics for both nondegenerate and degenerate cases. The distributed weighted bootstrap for the distributed two‐sample U‐statistic is new in the literature. The proposed bootstrap procedures are computationally efficient and are suitable for distributed computing platforms with theoretical guarantees. Extensive numerical studies illustrate that the proposed distributed approaches are feasible and effective.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"1090 - 1115"},"PeriodicalIF":1.0,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43213317","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
Inference for low‐ and high‐dimensional inhomogeneous Gibbs point processes 低维和高维非齐次吉布斯点过程的推论
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-09-30 DOI: 10.1111/sjos.12616
Ismaila Ba, Jean‐François Coeurjolly
{"title":"Inference for low‐ and high‐dimensional inhomogeneous Gibbs point processes","authors":"Ismaila Ba, Jean‐François Coeurjolly","doi":"10.1111/sjos.12616","DOIUrl":"https://doi.org/10.1111/sjos.12616","url":null,"abstract":"Gibbs point processes (GPPs) constitute a large and flexible class of spatial point processes with explicit dependence between the points. They can model attractive as well as repulsive point patterns. Feature selection procedures are an important topic in high‐dimensional statistical modeling. In this paper, a composite likelihood (in particular pseudo‐likelihood) approach regularized with convex and nonconvex penalty functions is proposed to handle statistical inference for possibly high‐dimensional inhomogeneous GPPs. We particularly investigate the setting where the number of covariates diverges as the domain of observation increases. Under some conditions provided on the spatial GPP and on penalty functions, we show that the oracle property, consistency and asymptotic normality hold. Our results also cover the low‐dimensional case which fills a large gap in the literature. Through simulation experiments, we validate our theoretical results and finally, an application to a tropical forestry dataset illustrates the use of the proposed approach.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"1021 - 993"},"PeriodicalIF":1.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45966747","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
On the robustness to outliers of the Student‐t process 关于Student - t过程对异常值的鲁棒性
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-09-06 DOI: 10.1111/sjos.12611
J. Andrade
{"title":"On the robustness to outliers of the Student‐t process","authors":"J. Andrade","doi":"10.1111/sjos.12611","DOIUrl":"https://doi.org/10.1111/sjos.12611","url":null,"abstract":"The theory of Bayesian robustness modeling uses heavy‐tailed distributions to resolve conflicts of information by rejecting automatically the outlying information in favor of the other sources of information. In particular, the Student's‐t process is a natural alternative to the Gaussian process when the data might carry atypical information. Several works attest to the robustness of the Student t$$ t $$ process, however, the studies are mostly guided by intuition and focused mostly on the computational aspects rather than the mathematical properties of the involved distributions. This work uses the theory of regular variation to address the robustness of the Student t$$ t $$ process in the context of nonlinear regression, that is, the behavior of the posterior distribution in the presence of outliers in the inputs, in the outputs, or in both sources of information. In all these cases, under certain conditions, it is shown that the posterior distribution tends to a quantity that does not depend on the atypical information, then, for every case, the limiting posterior distribution as the outliers tend to infinity is provided. The impact of outliers on the predictive posterior distribution is also addressed. The theory is illustrated with a few simulated examples.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"725 - 749"},"PeriodicalIF":1.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47392318","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
Nonparametric asymptotic confidence intervals for extreme quantiles 极值分位数的非参数渐近置信区间
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-09-06 DOI: 10.1111/sjos.12610
L. Gardes, Samuel Maistre
{"title":"Nonparametric asymptotic confidence intervals for extreme quantiles","authors":"L. Gardes, Samuel Maistre","doi":"10.1111/sjos.12610","DOIUrl":"https://doi.org/10.1111/sjos.12610","url":null,"abstract":"In this paper, we propose new asymptotic confidence intervals for extreme quantiles, that is, for quantiles located outside the range of the available data. We restrict ourselves to the situation where the underlying distribution is heavy‐tailed. While asymptotic confidence intervals are mostly constructed around a pivotal quantity, we consider here an alternative approach based on the distribution of order statistics sampled from a uniform distribution. The convergence of the coverage probability to the nominal one is established under a classical second‐order condition. The finite sample behavior is also examined and our methodology is applied to a real dataset.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"825 - 841"},"PeriodicalIF":1.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47579507","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
A conversation with Elja Arjas (Helsinki, November 2021 and March 2022) 与Elja Arjas的对话(赫尔辛基，2021年11月和2022年3月)
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2022-09-05 DOI: 10.1111/sjos.12612
J. Corander
{"title":"A conversation with Elja Arjas (Helsinki, November 2021 and March 2022)","authors":"J. Corander","doi":"10.1111/sjos.12612","DOIUrl":"https://doi.org/10.1111/sjos.12612","url":null,"abstract":"Statistics as an independent scientific discipline is relatively young in Finland. Its active history stretches back roughly a century, with the past 50 years signifying a period of growth. Few other academics such as Elja Arjas, now professor emeritus at University of Helsinki, have played a prominent role in establishing statistics in Finland. This conversation tries to illuminate how this came to happen and what was needed to push statistics as a discipline to a firmer ground. We do not have a looking glass at our disposal but will nevertheless also try make some predictions about the future.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":"12 - 3"},"PeriodicalIF":1.0,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44161588","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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