发布求助
文献互助 智能选刊 最新文献

Journal of the Royal Statistical Society Series C-Applied Statistics最新文献

筛选
英文 中文
A Tweedie Markov process and its application in fisheries stock assessment Tweedie Markov过程及其在渔业资源评价中的应用
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-07-20 DOI: 10.1093/jrsssc/qlad064
Nan Zheng, Y. Lim, N. Cadigan
{"title":"A Tweedie Markov process and its application in fisheries stock assessment","authors":"Nan Zheng, Y. Lim, N. Cadigan","doi":"10.1093/jrsssc/qlad064","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad064","url":null,"abstract":"\u0000 The Tweedie distribution is a useful tool to model zero-inflated non-negative continuous data. However, the Tweedie dispersion relationship (DR) is not general enough to cover some important forms such as quadratic dispersion, and an easy and fast-to-implement Tweedie AR(1) model (first-order autoregressive model) needs to be developed for spatio-temporal modelling. In this research we extend the Tweedie distribution to accommodate flexible DRs, and propose a Tweedie Markov process (TMP) with the AR(1) autocorrelation structure. This TMP is simple to implement and requires only the Tweedie probability density function. Simulation studies and real data analysis are conducted to validate our new approach.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"377 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80608354","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
Estimating default probabilities for no- and low-default portfolios: parameter specification via floor constraints 估计无违约和低违约投资组合的违约概率:通过下限约束的参数规范
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-07-14 DOI: 10.1093/jrsssc/qlad061
Oliver Blümke
{"title":"Estimating default probabilities for no- and low-default portfolios: parameter specification via floor constraints","authors":"Oliver Blümke","doi":"10.1093/jrsssc/qlad061","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad061","url":null,"abstract":"\u0000 For low- and no-default portfolios, financial institutions are confronted with the problem to estimate default probabilities for credit ratings for which no default was observed. The Bayesian approach offers a solution but brings the problem of the parameter assignment of the prior distribution. Sequential Bayesian updating allows to settle the question of the location parameter or mean of the prior distribution. This article proposes to use floor constraints to determine the scale or standard deviation parameter of the prior distribution. The floor constraint can also be used to determine the free parameter γ in the Pluto–Tasche approach.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"75 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82128012","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
Automated calibration for stability selection in penalised regression and graphical models. 在惩罚回归和图形模型中自动校准稳定性选择。
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-07-13 eCollection Date: 2023-11-01 DOI: 10.1093/jrsssc/qlad058
Barbara Bodinier, Sarah Filippi, Therese Haugdahl Nøst, Julien Chiquet, Marc Chadeau-Hyam
{"title":"Automated calibration for stability selection in penalised regression and graphical models.","authors":"Barbara Bodinier, Sarah Filippi, Therese Haugdahl Nøst, Julien Chiquet, Marc Chadeau-Hyam","doi":"10.1093/jrsssc/qlad058","DOIUrl":"10.1093/jrsssc/qlad058","url":null,"abstract":"<p><p>Stability selection represents an attractive approach to identify sparse sets of features jointly associated with an outcome in high-dimensional contexts. We introduce an automated calibration procedure via maximisation of an in-house stability score and accommodating a priori-known block structure (e.g. multi-OMIC) data. It applies to [Least Absolute Shrinkage Selection Operator (LASSO)] penalised regression and graphical models. Simulations show our approach outperforms non-stability-based and stability selection approaches using the original calibration. Application to multi-block graphical LASSO on real (epigenetic and transcriptomic) data from the Norwegian Women and Cancer study reveals a central/credible and novel cross-OMIC role of LRRN3 in the biological response to smoking. Proposed approaches were implemented in the R package sharp.</p>","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"72 5","pages":"1375-1393"},"PeriodicalIF":1.6,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10746547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139032725","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
Identification of taxon through classification with partial reject options 通过部分拒绝选项的分类识别分类单元
4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-07-01 DOI: 10.1093/jrsssc/qlad036
Måns Karlsson, Ola Hössjer
{"title":"Identification of taxon through classification with partial reject options","authors":"Måns Karlsson, Ola Hössjer","doi":"10.1093/jrsssc/qlad036","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad036","url":null,"abstract":"Abstract Identification of taxa can significantly be assisted by statistical classification based on trait measurements either individually or by phylogenetic (clustering) methods. In this article, we present a general Bayesian approach for classifying species individually based on measurements of a mixture of continuous and ordinal traits, and any type of covariates. The trait vector is derived from a latent variable with a multivariate Gaussian distribution. Decision rules based on supervised learning are presented that estimate model parameters through blocked Gibbs sampling. These decision regions allow for uncertainty (partial rejection), so that not necessarily one specific category (taxon) is output when new subjects are classified, but rather a set of categories including the most probable taxa. This type of discriminant analysis employs reward functions with a set-valued input argument, so that an optimal Bayes classifier can be defined. We also present a way of safeguarding against outlying new observations, using an analogue of a p-value within our Bayesian setting. We refer to our Bayesian set-valued classifier as the Karlsson–Hössjer method, and it is illustrated on an original ornithological data set of birds. We also incorporate model selection through cross-validation, exemplified on another original data set of birds.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136260255","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 design utility approach for preferentially sampled spatial data 优先采样空间数据的设计实用方法
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-30 DOI: 10.1093/jrsssc/qlad040
Elizabeth J Gray, E. Evangelou
{"title":"A design utility approach for preferentially sampled spatial data","authors":"Elizabeth J Gray, E. Evangelou","doi":"10.1093/jrsssc/qlad040","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad040","url":null,"abstract":"\u0000 Spatial preferential sampling occurs when the choice of sampling locations depends stochastically on the process of interest. Ignoring this dependence leads to inaccurate inferences. Our framework models experimenter preferences jointly with the spatial process to adjust for this. We dispense with the unrealistic assumption (required by existing methods) of conditional independence of sampling locations by defining a whole design distribution proportional to a utility function on the space of designs. The proposed model likelihood is generally intractable. We provide fitting techniques based on the noisy Markov chain Monte Carlo and demonstrate their usage on a data set of spatially distributed ammonia concentrations.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"17 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81990291","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
Daniel Clarkson, Emma Eastoe and Amber Leeson's (Lancaster University) reply to the Discussion of ‘Statistical aspects of climate change’ 丹尼尔·克拉克森、艾玛·伊斯特奥和安布尔·李森(兰开斯特大学)对“气候变化的统计方面”讨论的答复
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-28 DOI: 10.1093/jrsssc/qlad059
D. Clarkson, E. Eastoe, A. Leeson
{"title":"Daniel Clarkson, Emma Eastoe and Amber Leeson's (Lancaster University) reply to the Discussion of ‘Statistical aspects of climate change’","authors":"D. Clarkson, E. Eastoe, A. Leeson","doi":"10.1093/jrsssc/qlad059","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad059","url":null,"abstract":"","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"34 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75588026","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
Anna Choi and Tze Leung Lai’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’ 蔡安娜及策良来在“气候变化统计方面的第一次讨论会议”上的发言
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-22 DOI: 10.1093/jrsssc/qlad050
Anna Choi, T. Lai
{"title":"Anna Choi and Tze Leung Lai’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’","authors":"Anna Choi, T. Lai","doi":"10.1093/jrsssc/qlad050","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad050","url":null,"abstract":"","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"96 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85300919","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
Richard L Smith’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’ Richard L Smith对“气候变化统计方面的第一次讨论会议”讨论的贡献
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-22 DOI: 10.1093/jrsssc/qlad046
Richard L. Smith
{"title":"Richard L Smith’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’","authors":"Richard L. Smith","doi":"10.1093/jrsssc/qlad046","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad046","url":null,"abstract":"","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"31 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74066061","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
Two-dimensional fused targeted ridge regression for health indicator prediction from accelerometer data 二维融合目标脊回归用于加速度计数据健康指标预测
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-20 DOI: 10.1093/jrsssc/qlad041
A. Lettink, M. Chinapaw, W. V. van Wieringen
{"title":"Two-dimensional fused targeted ridge regression for health indicator prediction from accelerometer data","authors":"A. Lettink, M. Chinapaw, W. V. van Wieringen","doi":"10.1093/jrsssc/qlad041","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad041","url":null,"abstract":"\u0000 We present the two-dimensional targeted fused ridge estimator of the linear and logistic regression models. The estimator (i) handles both unpenalised and penalised covariates, (ii) accommodates possible relations among the covariates’ coefficients through a fusion penalty, and (iii) incorporates prior information on the regression parameter through a non-zero shrinkage target. In this work, the aforementioned relations are similarities among the covariates’ coefficients due to spatial proximity in a two-dimensional grid. In an extensive re-analysis of an epidemiological and an image analysis study, we illustrate the use of the estimator’s aforementioned features that result in a tangibly interpretable predictor.","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"1 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90622524","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
Christine P Chai’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’ 柴静雯在“气候变化统计方面的第一次讨论会议”上的发言
IF 1.6 4区 数学
Journal of the Royal Statistical Society Series C-Applied Statistics Pub Date : 2023-06-19 DOI: 10.1093/jrsssc/qlad049
Christine P Chai
{"title":"Christine P Chai’s contribution to the Discussion of ‘The First Discussion Meeting on Statistical aspects of climate change’","authors":"Christine P Chai","doi":"10.1093/jrsssc/qlad049","DOIUrl":"https://doi.org/10.1093/jrsssc/qlad049","url":null,"abstract":"","PeriodicalId":49981,"journal":{"name":"Journal of the Royal Statistical Society Series C-Applied Statistics","volume":"7 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75429227","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信