Journal of Statistical Planning and Inference最新文献_第10页

Construction of optimal supersaturated designs by the expansive replacement method 用膨胀置换法构造过饱和优化设计

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-11-10 DOI: 10.1016/j.jspi.2023.106118

Hui Li , Liuqing Yang , Kashinath Chatterjee , Min-Qian Liu

引用次数: 0

A pair of novel priors for improving and extending the conditional MLE 一对改进和扩展条件MLE的新先验

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-11-10 DOI: 10.1016/j.jspi.2023.106117

Takemi Yanagimoto , Yoichi Miyata

引用次数: 0

Generic E-variables for exact sequential k-sample tests that allow for optional stopping 通用e变量的精确顺序k-样本测试，允许可选的停止

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-10-26 DOI: 10.1016/j.jspi.2023.106116

Rosanne J. Turner , Alexander Ly , Peter D. Grünwald

{"title":"Generic E-variables for exact sequential k-sample tests that allow for optional stopping","authors":"Rosanne J. Turner , Alexander Ly , Peter D. Grünwald","doi":"10.1016/j.jspi.2023.106116","DOIUrl":"https://doi.org/10.1016/j.jspi.2023.106116","url":null,"abstract":"<div>We develop <math><mstyle><mi>E</mi></mstyle></math>-variables for testing whether two or more data streams come from the same source or not, and more generally, whether the difference between the sources is larger than some minimal effect size. These <math><mstyle><mi>E</mi></mstyle></math>-variables lead to exact, nonasymptotic tests that remain safe, i.e., keep their type-I error guarantees, under flexible sampling scenarios such as optional stopping and continuation. In special cases our <math><mstyle><mi>E</mi></mstyle></math>-variables also have an optimal ‘growth’ property under the alternative. While the construction is generic, we illustrate it through the special case of <math><mrow><mi>k</mi><mo>×</mo><mn>2</mn></mrow></math> contingency tables, i.e. <math><mi>k</mi></math> Bernoulli streams, allowing for the incorporation of different restrictions on the composite alternative. Comparison to <math><mi>p</mi></math>-value analysis in simulations and a real-world 2 × 2 contingency table example show that <math><mstyle><mi>E</mi></mstyle></math>-variables, through their flexibility, often allow for early stopping of data collection — thereby retaining similar power as classical methods — while also retaining the option of extending or combining data afterwards.</div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S037837582300085X/pdfft?md5=572bc8e92c25baa3e6a3f4936ee83e72&pid=1-s2.0-S037837582300085X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92043596","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

A comparison of likelihood-based methods for size-biased sampling 基于可能性的大小偏差抽样方法的比较

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-10-13 DOI: 10.1016/j.jspi.2023.106115

Victoria L. Leaver , Robert G. Clark , Pavel N. Krivitsky , Carole L. Birrell

{"title":"A comparison of likelihood-based methods for size-biased sampling","authors":"Victoria L. Leaver , Robert G. Clark , Pavel N. Krivitsky , Carole L. Birrell","doi":"10.1016/j.jspi.2023.106115","DOIUrl":"https://doi.org/10.1016/j.jspi.2023.106115","url":null,"abstract":"<div>Three likelihood approaches to estimation under informative sampling are compared using a special case for which analytic expressions are possible to derive. An independent and identically distributed population of values of a variable of interest is drawn from a gamma distribution, with the shape parameter and the population size both assumed to be known. The sampling method is selection with probability proportional to a power of the variable with replacement, so that duplicate sample units are possible. Estimators of the unknown parameter, variance estimators and asymptotic variances of the estimators are derived for maximum likelihood, sample likelihood and pseudo-likelihood estimation. Theoretical derivations and simulation results show that the efficiency of the sample likelihood approaches that of full maximum likelihood estimation when the sample size <math><mi>n</mi></math> tends to infinity and the sampling fraction <math><mi>f</mi></math> tends to zero. However, when <math><mi>n</mi></math> tends to infinity and <math><mi>f</mi></math> is not negligible, the maximum likelihood estimator is more efficient than the other methods because it takes the possibility of duplicate sample units into account. Pseudo-likelihood can perform much more poorly than the other methods in some cases. For the special case when the superpopulation is exponential and the selection is probability proportional to size, the anticipated variance of the pseudo-likelihood estimate is infinite.</div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378375823000848/pdfft?md5=34807a0d3caadad51aaee1e2b82b751e&pid=1-s2.0-S0378375823000848-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92115764","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

Maximum likelihood estimation of the log-concave component in a semi-parametric mixture with a standard normal density 具有标准正态密度的半参数混合物中对数凹分量的最大似然估计

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-10-07 DOI: 10.1016/j.jspi.2023.106113

Fadoua Balabdaoui, Harald Besdziek

引用次数: 0

Regression models for circular data based on nonnegative trigonometric sums 基于非负三角和的循环数据回归模型

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-09-27 DOI: 10.1016/j.jspi.2023.106114

Juan José Fernández-Durán, María Mercedes Gregorio-Domínguez

引用次数: 0

Time changes and stationarity issues for extended scalar autoregressive models 扩展标量自回归模型的时间变化和平稳性问题

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-09-23 DOI: 10.1016/j.jspi.2023.106112

V. Girardin , R. Senoussi

引用次数: 0

Testing higher and infinite degrees of stochastic dominance for small samples: A Bayesian approach 测试小样本的更高和无限程度的随机优势:贝叶斯方法

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-09-17 DOI: 10.1016/j.jspi.2023.106102

Mariusz Górajski

{"title":"Testing higher and infinite degrees of stochastic dominance for small samples: A Bayesian approach","authors":"Mariusz Górajski","doi":"10.1016/j.jspi.2023.106102","DOIUrl":"https://doi.org/10.1016/j.jspi.2023.106102","url":null,"abstract":"<div>This study proposes a distribution-free Bayesian procedure that detects infinite degrees of stochastic dominance (SD<math><mi>∞</mi></math>) between two random outcomes and then seeks a finite degree <math><mrow><mi>k</mi><mo>≥</mo><mn>1</mn></mrow></math> of stochastic dominance (SD<math><mi>k</mi></math>). Based on small samples, we construct four-choice Bayesian tests by combining an encompassing prior Bayesian model with the Dirichlet process priors that discriminate between SD<math><mi>∞</mi></math> and SD<math><mi>k</mi></math> of one random variable over the other with non-dominance or equality between them. We use Monte Carlo simulations to evaluate the novel Bayesian tests for SD<math><mi>k</mi></math> and SD<math><mi>∞</mi></math> and compare them to the subsampling and bootstrap significance tests for SD<math><mi>k</mi></math>. Our simulation shows that the Bayesian tests for SD<math><mi>k</mi></math> outperform the significance tests for small samples, especially for detecting non-stochastic dominance. This study shows that the test for SD<math><mi>∞</mi></math> is an accurate decision-making tool when using small samples.</div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49903456","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

Publishers Note 出版商注意

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-09-13 DOI: 10.1016/S0378-3758(23)00076-9

引用次数: 0

Weighted bootstrap for two-sample U-statistics 两样本u统计量的加权自举

IF 0.9 4区数学

Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.02.004

Bingyao Huang , Yanyan Liu , Liuhua Peng

引用次数: 0