Australian & New Zealand Journal of Statistics最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148086249","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}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148079815","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}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148072707","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}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148100211","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}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148097159","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}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148076612","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}

{"title":"R Environments, Scoping, and Evaluation With Some Applications","authors":"Ross Ihaka","doi":"10.1111/anzs.70044","DOIUrl":"https://doi.org/10.1111/anzs.70044","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper aims to expose one of <span>R</span>'s important features that seems to be little-known by most users. The particular feature is language scoping, which <span>R</span> inherits from languages like <span>Algol60</span> and <span>Scheme</span>. Although the feature is comparatively little known, it is quite important, and knowing about it can change the way that <span>R</span> is used. Rather than proceeding as a technical exposition, the content is presented as a series of examples. These are formatted (without continuation prompts) so that they are easy to copy and paste. The right way to read the paper is to copy the examples and experiment with them.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/anzs.70044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147686243","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}

{"title":"Editorial: 25 YeaRs (Special Issue)","authors":"Tilman M. Davies","doi":"10.1111/anzs.70046","DOIUrl":"https://doi.org/10.1111/anzs.70046","url":null,"abstract":"","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615245","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}

{"title":"Optimal Estimation for a Class of High-Dimensional Covariance Matrices","authors":"Huimin Li,&nbsp;Youming Liu","doi":"10.1111/anzs.70047","DOIUrl":"https://doi.org/10.1111/anzs.70047","url":null,"abstract":"<div>\u0000 \u0000 <p>Estimation of large covariance matrices plays important roles in high-dimensional data analysis. The sub-Gaussian condition of a random vector is usually assumed, which requires the existence of infinite moments. Avella-Medina et al. (2018) provide an upper bound estimation in the sense of probability over a sparse covariance matrix space under the weak assumption of bounded <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>2</mn>\u0000 <mo>+</mo>\u0000 <mi>ε</mi>\u0000 </mrow>\u0000 <annotation>$$ 2+varepsilon $$</annotation>\u0000 </semantics></math> moments (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>0</mn>\u0000 <mo>&lt;</mo>\u0000 <mi>ε</mi>\u0000 <mo>≤</mo>\u0000 <mn>2</mn>\u0000 </mrow>\u0000 <annotation>$$ 0&lt;varepsilon le 2 $$</annotation>\u0000 </semantics></math>), see Biometrika, 105, 271–284. In particular, their estimation attains the minimax optimality when <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>ε</mi>\u0000 <mo>=</mo>\u0000 <mn>2</mn>\u0000 </mrow>\u0000 <annotation>$$ varepsilon =2 $$</annotation>\u0000 </semantics></math>. The authors conjecture that their estimation is optimal as well for <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>ε</mi>\u0000 <mo>∈</mo>\u0000 <mo>(</mo>\u0000 <mn>0</mn>\u0000 <mo>,</mo>\u0000 <mn>2</mn>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation>$$ varepsilon in left(0,2right) $$</annotation>\u0000 </semantics></math>. In this paper, we first extend their upper bound estimation to a larger space and then prove the optimality of our estimation. This can be considered as a solution to their conjecture. Moreover, we give an optimal estimation in terms of expectation on the same space. Finally, numerical experiments support our theoretical analysis.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147569084","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}

{"title":"A Personal History of the tidyverse","authors":"Hadley Wickham","doi":"10.1111/anzs.70045","DOIUrl":"https://doi.org/10.1111/anzs.70045","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, I trace the evolution of the <span>tidyverse</span>, a cohesive ecosystem of <span>R</span> packages for data science. Beginning with early packages I created during my PhD at Iowa State University, I explain how they coalesced into a unified collection with consistent principles. I detail key innovations including tidy data, <span>tibbles</span>, the pipe operator, tidy evaluation and the role of hex stickers in community building. I describe the transition from my individual efforts to a collaborative enterprise supported by a team at <span>Posit</span> and a vibrant global community. I highlight the importance of human-centred design, consistency, composability and inclusivity as our guiding principles. I discuss how our recent priorities have shifted from innovation to maintenance as the ecosystem has matured. Looking to the future, I discuss our current areas of focus including <span>Positron</span> (a new data science IDE), <span>R</span> in production environments and integrating large language models into data science workflows.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"68 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147564491","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}