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Structure learning for continuous time Bayesian networks via penalized likelihood 通过惩罚似然法学习连续时间贝叶斯网络的结构
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-08-22 DOI: 10.1111/sjos.12747
Tomasz Ca̧kała, Błażej Miasojedow, Wojciech Rejchel, Maryia Shpak
{"title":"Structure learning for continuous time Bayesian networks via penalized likelihood","authors":"Tomasz Ca̧kała, Błażej Miasojedow, Wojciech Rejchel, Maryia Shpak","doi":"10.1111/sjos.12747","DOIUrl":"https://doi.org/10.1111/sjos.12747","url":null,"abstract":"Continuous time Bayesian networks (CTBNs) represent a class of stochastic processes, which can be used to model complex phenomena, for instance, they can describe interactions occurring in living processes, social science models or medicine. The literature on this topic is usually focused on a case when a dependence structure of a system is known and we are to determine conditional transition intensities (parameters of a network). In the paper, we study a structure learning problem, which is a more challenging task and the existing research on this topic is limited. The approach, which we propose, is based on a penalized likelihood method. We prove that our algorithm, under mild regularity conditions, recognizes a dependence structure of a graph with high probability. We also investigate properties of the procedure in numerical studies.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"50 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186967","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
Regression‐based network‐flow and inner‐matrix reconstruction 基于回归的网络流和内矩阵重构
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-23 DOI: 10.1111/sjos.12742
Michael Lebacher, Göran Kauermann
{"title":"Regression‐based network‐flow and inner‐matrix reconstruction","authors":"Michael Lebacher, Göran Kauermann","doi":"10.1111/sjos.12742","DOIUrl":"https://doi.org/10.1111/sjos.12742","url":null,"abstract":"Network or matrix reconstruction is a general problem that occurs if the row‐ and column sums of a matrix are given, and the matrix entries need to be predicted conditional on the aggregated information. In this paper, we show that the predictions obtained from the iterative proportional fitting procedure (IPFP) or equivalently maximum entropy (ME) can be obtained by restricted maximum likelihood estimation relying on augmented Lagrangian optimization. Based on this equivalence, we extend the framework of network reconstruction, conditional on row and column sums, toward regression, which allows the inclusion of exogenous covariates and bootstrap‐based uncertainty quantification. More specifically, the mean of the regression model leads to the observed row and column margins. To exemplify the approach, we provide a simulation study and investigate interbank lending data, provided by the Bank for International Settlement. This dataset provides full knowledge of the real network and is, therefore, suitable to evaluate the predictions of our approach. It is shown that the inclusion of exogenous information leads to superior predictions in terms of and errors.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"46 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780377","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 mixture models (in)consistency for the number of clusters 贝叶斯混合物模型在聚类数量方面的（不）一致性
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-23 DOI: 10.1111/sjos.12739
Louise Alamichel, Daria Bystrova, Julyan Arbel, Guillaume Kon Kam King
{"title":"Bayesian mixture models (in)consistency for the number of clusters","authors":"Louise Alamichel, Daria Bystrova, Julyan Arbel, Guillaume Kon Kam King","doi":"10.1111/sjos.12739","DOIUrl":"https://doi.org/10.1111/sjos.12739","url":null,"abstract":"Bayesian nonparametric mixture models are common for modeling complex data. While these models are well‐suited for density estimation, recent results proved posterior inconsistency of the number of clusters when the true number of components is finite, for the Dirichlet process and Pitman–Yor process mixture models. We extend these results to additional Bayesian nonparametric priors such as Gibbs‐type processes and finite‐dimensional representations thereof. The latter include the Dirichlet multinomial process, the recently proposed Pitman–Yor, and normalized generalized gamma multinomial processes. We show that mixture models based on these processes are also inconsistent in the number of clusters and discuss possible solutions. Notably, we show that a postprocessing algorithm introduced for the Dirichlet process can be extended to more general models and provides a consistent method to estimate the number of components.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"7 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780375","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 special section honoring Nils Lid Hjort 纪念尼尔斯-利德-希约尔特的专栏
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-23 DOI: 10.1111/sjos.12745
Ørnulf Borgan, Ingrid K. Glad
{"title":"A special section honoring Nils Lid Hjort","authors":"Ørnulf Borgan, Ingrid K. Glad","doi":"10.1111/sjos.12745","DOIUrl":"https://doi.org/10.1111/sjos.12745","url":null,"abstract":"","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"126 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780376","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 classical hypothesis test for assessing the homogeneity of disease transmission in stochastic epidemic models 用于评估随机流行病模型中疾病传播同质性的经典假设检验
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-19 DOI: 10.1111/sjos.12743
Georgios Aristotelous, Theodore Kypraios, Philip D. O'Neill
{"title":"A classical hypothesis test for assessing the homogeneity of disease transmission in stochastic epidemic models","authors":"Georgios Aristotelous, Theodore Kypraios, Philip D. O'Neill","doi":"10.1111/sjos.12743","DOIUrl":"https://doi.org/10.1111/sjos.12743","url":null,"abstract":"This paper addresses the problem of assessing the homogeneity of the disease transmission process in stochastic epidemic models in populations that are partitioned into social groups. We develop a classical hypothesis test for completed epidemics which assesses whether or not there is significant within‐group transmission during an outbreak. The test is based on time‐ordered group labels of individuals. The null hypothesis is that of homogeneity of disease transmission among individuals, a hypothesis under which the discrete random vector of groups labels has a known sampling distribution that is independent of any model parameters. The test exhibits excellent performance when applied to various scenarios of simulated data and is also illustrated using two real‐life epidemic data sets. We develop some asymptotic theory including a central limit theorem. The test is practically very appealing, being computationally cheap and straightforward to implement, as well as being applicable to a wide range of real‐life outbreak settings and to related problems in other fields.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"61 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141738111","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
Minimax rate of estimation for invariant densities associated to continuous stochastic differential equations over anisotropic Hölder classes 各向异性荷尔德类上与连续随机微分方程相关的不变量密度的最小估计率
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-11 DOI: 10.1111/sjos.12735
Chiara Amorino, Arnaud Gloter
{"title":"Minimax rate of estimation for invariant densities associated to continuous stochastic differential equations over anisotropic Hölder classes","authors":"Chiara Amorino, Arnaud Gloter","doi":"10.1111/sjos.12735","DOIUrl":"https://doi.org/10.1111/sjos.12735","url":null,"abstract":"We study the problem of the nonparametric estimation for the density of the stationary distribution of a ‐dimensional stochastic differential equation . From the continuous observation of the sampling path on , we study the estimation of as goes to infinity. For , we characterize the minimax rate for the ‐risk in pointwise estimation over a class of anisotropic Hölder functions with regularity . For , our finding is that, having ordered the smoothness such that , the minimax rate depends on whether or . In the first case, this rate is , and in the second case, it is , where is an explicit exponent dependent on the dimension and , the harmonic mean of smoothness over the directions after excluding and , the smallest ones. We also demonstrate that kernel‐based estimators achieve the optimal minimax rate. Furthermore, we propose an adaptive procedure for both integrated and pointwise risk. In the two‐dimensional case, we show that kernel density estimators achieve the rate , which is optimal in the minimax sense. Finally we illustrate the validity of our theoretical findings by proposing numerical results.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"32 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614551","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
Estimation of win, loss probabilities, and win ratio based on right‐censored event data 基于右删失事件数据的胜负概率和胜率估计
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-04 DOI: 10.1111/sjos.12734
Erik T. Parner, Morten Overgaard
{"title":"Estimation of win, loss probabilities, and win ratio based on right‐censored event data","authors":"Erik T. Parner, Morten Overgaard","doi":"10.1111/sjos.12734","DOIUrl":"https://doi.org/10.1111/sjos.12734","url":null,"abstract":"The win ratio has in the recent decade gained popularity for analyzing prioritized multiple event data in clinical cohort studies, in particular within cardiovascular research. The literature on estimation of the win ratio using censored event data is however sparse. The methods that have been suggested have either an insufficient adjustment of the censoring or by assuming the the win and loss probabilities are proportional over time. The assumption of proportional win and loss probabilities will often in practice not be satisfied. In this paper, we present estimates for the win ratio, and win and loss probabilities, under independent right‐censoring and derive the asymptotic distribution of the estimates. The proposed win ratio estimate does not require the assumption of proportional win and loss probabilities. The small sample properties of the proposed method are studied in a simulation study showing that the variance formula is accurate even for small samples. The method is applied on two data sets.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"19 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548567","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
Commentary on “Pitfalls of amateur regression: The Dutch New Herring controversies” 关于 "业余回归的陷阱：荷兰新鲱鱼之争"
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-04 DOI: 10.1111/sjos.12741
Jan C. Van Ours, Ben Vollaard
{"title":"Commentary on “Pitfalls of amateur regression: The Dutch New Herring controversies”","authors":"Jan C. Van Ours, Ben Vollaard","doi":"10.1111/sjos.12741","DOIUrl":"https://doi.org/10.1111/sjos.12741","url":null,"abstract":"","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"37 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548566","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 densities on the hypersphere using a parametric guide 使用参数指南对超球面上的密度进行非参数估计
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-03 DOI: 10.1111/sjos.12737
María Alonso‐Pena, Gerda Claeskens, Irène Gijbels
{"title":"Nonparametric estimation of densities on the hypersphere using a parametric guide","authors":"María Alonso‐Pena, Gerda Claeskens, Irène Gijbels","doi":"10.1111/sjos.12737","DOIUrl":"https://doi.org/10.1111/sjos.12737","url":null,"abstract":"Hyperspherical kernel density estimators (KDE), which use a parametric distribution as a guide, are studied in this paper. The main benefit is that these estimators improve the bias of nonguided kernel density estimators when the parametric guiding distribution is not too far from the true density, while preserving the variance. When using a von Mises‐Fisher density as guide, the proposal performs as well as the classical KDE, even when the guiding model is incorrect, and far from the true distribution. This benefit is particular for the hyperspherical setting given its compact support, and is in contrast to similar methods for real valued data. Moreover, we deal with the important issue of data‐driven selection of the smoothing parameter. Simulations and real data examples illustrate the finite‐sample performance of the proposed method, also in comparison with other recently proposed estimation methods.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"24 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548569","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
Lancaster correlation: A new dependence measure linked to maximum correlation 兰开斯特相关性：与最大相关性相关联的一种新的依赖性测量方法
IF 1 4区 数学
Scandinavian Journal of Statistics Pub Date : 2024-07-03 DOI: 10.1111/sjos.12733
Hajo Holzmann, Bernhard Klar
{"title":"Lancaster correlation: A new dependence measure linked to maximum correlation","authors":"Hajo Holzmann, Bernhard Klar","doi":"10.1111/sjos.12733","DOIUrl":"https://doi.org/10.1111/sjos.12733","url":null,"abstract":"We suggest novel correlation coefficients which equal the maximum correlation for a class of bivariate Lancaster distributions while being only slightly smaller than maximum correlation for a variety of further bivariate distributions. In contrast to maximum correlation, however, our correlation coefficients allow for rank and moment‐based estimators which are simple to compute and have tractable asymptotic distributions. Confidence intervals resulting from these asymptotic approximations and the covariance bootstrap show good finite‐sample coverage. In a simulation, the power of asymptotic as well as permutation tests for independence based on our correlation measures compares favorably with competing methods based on distance correlation or rank coefficients for functional dependence, among others. Moreover, for the bivariate normal distribution, our correlation coefficients equal the absolute value of the Pearson correlation, an attractive feature for practitioners which is not shared by various competitors. We illustrate the practical usefulness of our methods in applications to two real data sets.","PeriodicalId":49567,"journal":{"name":"Scandinavian Journal of Statistics","volume":"56 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548568","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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