发布求助
文献互助 智能选刊 最新文献

Statistics & Probability Letters最新文献

筛选
英文 中文
3 × 3 optimal ranked set sampling design with k cycles and best linear invariant estimators of the parameters for normal distribution 具有k个周期的3 × 3最优排序集抽样设计和正态分布参数的最佳线性不变估计
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-05-14 DOI: 10.1016/j.spl.2025.110455
Minmin Li, Wangxue Chen
{"title":"3 × 3 optimal ranked set sampling design with k cycles and best linear invariant estimators of the parameters for normal distribution","authors":"Minmin Li,&nbsp;Wangxue Chen","doi":"10.1016/j.spl.2025.110455","DOIUrl":"10.1016/j.spl.2025.110455","url":null,"abstract":"<div><div>In statistical parameter estimation problems, how well the parameters are estimated largely depends on the sampling design used. Cost effective sampling will be an important research problem. In this article, we find a 3 × 3 optimal ranked set sampling (RSS) design with <span><math><mi>k</mi></math></span> cycles for the normal distribution <span><math><mrow><mi>N</mi><mrow><mo>(</mo><mi>μ</mi><mo>,</mo><msup><mrow><mi>σ</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span> in which the location parameter <span><math><mi>μ</mi></math></span> and the scale parameter <span><math><mi>σ</mi></math></span> are both unknown based on the D–optimal criterion in the experimental design. Then, the best linear invariant estimates (BLIEs) of <span><math><mi>μ</mi></math></span> and <span><math><mi>σ</mi></math></span> from <span><math><mrow><mi>N</mi><mrow><mo>(</mo><mi>μ</mi><mo>,</mo><msup><mrow><mi>σ</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span> and their properties are studied under this RSS design. The efficiency is compared by the determinant of the mean square error matrix. The theoretical results and numerical results show that the BLIEs under the optimal RSS are more effective than the BLIEs under the balanced RSS.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110455"},"PeriodicalIF":0.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948240","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 simple bootstrap method for large entropy unequal probability sampling designs 大熵不等概率抽样设计的简单自举方法
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-05-09 DOI: 10.1016/j.spl.2025.110442
Yves Tillé
{"title":"A simple bootstrap method for large entropy unequal probability sampling designs","authors":"Yves Tillé","doi":"10.1016/j.spl.2025.110442","DOIUrl":"10.1016/j.spl.2025.110442","url":null,"abstract":"<div><div>We propose a simple bootstrap method for large entropy unequal probability sampling designs for finite populations. The method belongs to the class of bootstrap techniques that generate replication weights directly for the sampled units. It produces integer replication weights and is applicable to both equal and unequal probability designs characterized by high entropy, such as randomized systematic, pivotal, and maximum entropy designs. Our approach relies on the Dirichlet-Multinomial distribution to generate bootstrap samples while ensuring desirable statistical properties. We provide an efficient implementation in <span>R</span> and validate the method through simulations using real-world data. Results show that the proposed bootstrap estimator performs comparably to established variance estimation techniques while offering greater flexibility for non-linear estimators.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110442"},"PeriodicalIF":0.9,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931544","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
Construction of mixed-level column-orthogonal strong orthogonal arrays of strength two plus 强度为2 +的混合级列正交强正交阵列的构造
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-05-06 DOI: 10.1016/j.spl.2025.110447
Chen Li, Yan Zhu, Shanqi Pang
{"title":"Construction of mixed-level column-orthogonal strong orthogonal arrays of strength two plus","authors":"Chen Li,&nbsp;Yan Zhu,&nbsp;Shanqi Pang","doi":"10.1016/j.spl.2025.110447","DOIUrl":"10.1016/j.spl.2025.110447","url":null,"abstract":"<div><div>Strong orthogonal arrays were introduced and studied as a class of space-filling designs for computer experiments. Column orthogonality is an important property in computer experiments. In this paper, using generalized multiplication, we introduce a new general method for obtaining mixed-level column-orthogonal strong orthogonal arrays (OSOAs) of strength two plus. We also use generator matrices and the expansive replacement method to obtain numerous new mixed-level OSOAs of strength two plus. The constructions offer convenience and flexibility in selecting factor levels and run sizes. As an application of these methods, the constructed OSOAs contain nearly all existing array classes as special cases. Some selective OSOAs are tabulated for practical uses.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110447"},"PeriodicalIF":0.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929513","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 simplified condition for quantile regression 分位数回归的简化条件
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-30 DOI: 10.1016/j.spl.2025.110444
Liang Peng , Yongcheng Qi
{"title":"A simplified condition for quantile regression","authors":"Liang Peng ,&nbsp;Yongcheng Qi","doi":"10.1016/j.spl.2025.110444","DOIUrl":"10.1016/j.spl.2025.110444","url":null,"abstract":"<div><div>Quantile regression is effective in modeling and inferring the conditional quantile given some predictors and has become popular in risk management due to wide applications of quantile-based risk measures. When forecasting risk for economic and financial variables, quantile regression has to account for heteroscedasticity, which raises the question of whether the identification condition on residuals in quantile regression is equivalent to one independent of heteroscedasticity. In this paper, we present some identification conditions under three probability models and use them to establish simplified conditions in quantile regression.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110444"},"PeriodicalIF":0.9,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899658","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
Inference for generalized additive mixed models via penalized marginal likelihood 基于惩罚边际似然的广义加性混合模型推理
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-26 DOI: 10.1016/j.spl.2025.110443
Alex Stringer
{"title":"Inference for generalized additive mixed models via penalized marginal likelihood","authors":"Alex Stringer","doi":"10.1016/j.spl.2025.110443","DOIUrl":"10.1016/j.spl.2025.110443","url":null,"abstract":"<div><div>The Laplace approximation is sometimes not sufficiently accurate for smoothing parameter estimation in generalized additive mixed models. A novel estimation strategy is proposed that solves this problem and leads to estimates exhibiting the correct statistical properties.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110443"},"PeriodicalIF":0.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888241","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
Exact simulation of the Marchenko–Pastur distribution Marchenko-Pastur分布的精确模拟
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-26 DOI: 10.1016/j.spl.2025.110440
Luc Devroye
{"title":"Exact simulation of the Marchenko–Pastur distribution","authors":"Luc Devroye","doi":"10.1016/j.spl.2025.110440","DOIUrl":"10.1016/j.spl.2025.110440","url":null,"abstract":"<div><div>The Marchenko–Pastur law (Marchenko and Pastur, 1967) describes the limit law of eigenvalues of large rectangular matrices. We give two efficient algorithms for simulating random variables from this distribution.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110440"},"PeriodicalIF":0.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143881645","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
Automatic Transfer Learning for high-dimensional linear regression 高维线性回归的自动迁移学习
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-26 DOI: 10.1016/j.spl.2025.110445
Xinhao Qu
{"title":"Automatic Transfer Learning for high-dimensional linear regression","authors":"Xinhao Qu","doi":"10.1016/j.spl.2025.110445","DOIUrl":"10.1016/j.spl.2025.110445","url":null,"abstract":"<div><div>Transferability/Transportability has continuously been the central topic for transfer learning tasks, this paper designs <em>Automatic Transfer Learning</em> (ATL) that embeds such information within the learning process automatically. We demonstrate that, under high-dimensional linear setting, ATL estimator is doubly robust for negative transfer and achieves optimal rate under certain conditions. Numerical implementations also show its efficacy.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110445"},"PeriodicalIF":0.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143890529","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
Edgeworth expansion for semi-hard triplet loss 半硬三重态损失的Edgeworth展开
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-23 DOI: 10.1016/j.spl.2025.110441
Masanari Kimura
{"title":"Edgeworth expansion for semi-hard triplet loss","authors":"Masanari Kimura","doi":"10.1016/j.spl.2025.110441","DOIUrl":"10.1016/j.spl.2025.110441","url":null,"abstract":"<div><div>We develop a higher-order asymptotic analysis for the semi-hard triplet loss using the Edgeworth expansion. It is known that this loss function enforces that embeddings of similar samples are close while those of dissimilar samples are separated by a specified margin. By refining the classical central limit theorem, our approach quantifies the impact of the margin parameter and the skewness of the underlying data distribution on the loss behavior. In particular, we derive explicit Edgeworth expansions that reveal first-order corrections in terms of the third cumulant, thereby characterizing non-Gaussian effects present in the distribution of distance differences between anchor-positive and anchor-negative pairs. Our findings provide detailed insight into the sensitivity of the semi-hard triplet loss to its parameters and offer guidance for choosing the margin to ensure training stability.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110441"},"PeriodicalIF":0.9,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869130","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
On reverse inequalities for Besov integral probability metrics between smooth densities 光滑密度间Besov积分概率度量的逆不等式
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-21 DOI: 10.1016/j.spl.2025.110437
Jeongjik Lee, Minwoo Chae
{"title":"On reverse inequalities for Besov integral probability metrics between smooth densities","authors":"Jeongjik Lee,&nbsp;Minwoo Chae","doi":"10.1016/j.spl.2025.110437","DOIUrl":"10.1016/j.spl.2025.110437","url":null,"abstract":"<div><div>For smooth probability densities, we prove certain reverse inequalities between Besov integral probability metrics with different orders of smoothness. Our results provide a substantial generalization and improvement of the existing results in the literature.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110437"},"PeriodicalIF":0.9,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863515","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 note on the long time behavior of the elephant random walk with stops 关于大象随停随机行走的长时间行为的注释
IF 0.9 4区 数学
Statistics & Probability Letters Pub Date : 2025-04-19 DOI: 10.1016/j.spl.2025.110436
Tatsuya Akimoto , Masato Takei , Keisuke Taniguchi
{"title":"A note on the long time behavior of the elephant random walk with stops","authors":"Tatsuya Akimoto ,&nbsp;Masato Takei ,&nbsp;Keisuke Taniguchi","doi":"10.1016/j.spl.2025.110436","DOIUrl":"10.1016/j.spl.2025.110436","url":null,"abstract":"<div><div>We study the long time behavior of the elephant random walk with stops, introduced by Kumar, Harbola and Lindenberg (2010), and establish the phase transition of the number of visited points up to time <span><math><mi>n</mi></math></span>, and the correlation between the position at time <span><math><mi>n</mi></math></span> and the number of moves up to time <span><math><mi>n</mi></math></span>.</div></div>","PeriodicalId":49475,"journal":{"name":"Statistics & Probability Letters","volume":"224 ","pages":"Article 110436"},"PeriodicalIF":0.9,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864408","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
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