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Journal of Statistical Planning and Inference最新文献

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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
{"title":"Time changes and stationarity issues for extended scalar autoregressive models","authors":"V. Girardin ,&nbsp;R. Senoussi","doi":"10.1016/j.jspi.2023.106112","DOIUrl":"https://doi.org/10.1016/j.jspi.2023.106112","url":null,"abstract":"<div><p>A scalar discrete or continuous time process is reducible to stationarity (RWS) if its transform by some smooth time change is weakly stationary. Different issues linked to this notion are here investigated for autoregressive (AR) models. AR models are understood in a large sense and may have time-varying coefficients. In the continuous time case the innovation may be of the semi-martingale type–such as compound Poisson noise; in the discrete case, the noise may not be Gaussian.</p><p>Necessary and sufficient conditions for scalar AR models to be RWS are investigated, with explicit formulas for the time changes. Stationarity reduction issues for discrete sequences sampled from time continuous AR processes are also considered. Several types of time changes, RWS processes and sequences are studied with examples and simulation, including the classical multiplicative stationary AR models.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49903458","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
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><p><span>This study proposes a distribution-free Bayesian procedure that detects infinite degrees of stochastic dominance (SD</span><span><math><mi>∞</mi></math></span>) between two random outcomes and then seeks a finite degree <span><math><mrow><mi>k</mi><mo>≥</mo><mn>1</mn></mrow></math></span> of stochastic dominance (SD<span><math><mi>k</mi></math></span><span>). 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</span><span><math><mi>∞</mi></math></span> and SD<span><math><mi>k</mi></math></span> 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<span><math><mi>k</mi></math></span> and SD<span><math><mi>∞</mi></math></span> and compare them to the subsampling and bootstrap significance tests for SD<span><math><mi>k</mi></math></span>. Our simulation shows that the Bayesian tests for SD<span><math><mi>k</mi></math></span> outperform the significance tests for small samples, especially for detecting non-stochastic dominance. This study shows that the test for SD<span><math><mi>∞</mi></math></span> is an accurate decision-making tool when using small samples.</p></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
{"title":"Publishers Note","authors":"","doi":"10.1016/S0378-3758(23)00076-9","DOIUrl":"https://doi.org/10.1016/S0378-3758(23)00076-9","url":null,"abstract":"","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49877387","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
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
{"title":"Weighted bootstrap for two-sample U-statistics","authors":"Bingyao Huang ,&nbsp;Yanyan Liu ,&nbsp;Liuhua Peng","doi":"10.1016/j.jspi.2023.02.004","DOIUrl":"https://doi.org/10.1016/j.jspi.2023.02.004","url":null,"abstract":"<div><p><span>In this paper, we introduce weighted bootstrap algorithms for both non-degenerate and degenerate two-sample </span><span><math><mi>U</mi></math></span><span>-statistics with arbitrary degrees. For the non-degenerate case, weighted bootstrap with dependent weights is introduced as a generalization of Efron’s conventional bootstrap. In addition, two weighted bootstrap procedures with independent productive weights and independent additive weights are proposed under non-degeneracy. More importantly, we extend the weighted bootstrap method to two-sample </span><span><math><mi>U</mi></math></span><span><span>-statistics under the degeneracy of order 2 with a novel construction of random weights. Theoretical supports of the proposed weighted bootstrap procedures under non-degeneracy and degeneracy of order 2 are established. Numerical studies illustrate that the proposed approaches are feasible and effective for </span>statistical inferences.</span></p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49865498","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
Empirical likelihood in single-index quantile regression with high dimensional and missing observations 具有高维和缺失观测的单指标分位数回归的经验似然性
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.01.005
Bao-Hua Wang, Han-Ying Liang
{"title":"Empirical likelihood in single-index quantile regression with high dimensional and missing observations","authors":"Bao-Hua Wang,&nbsp;Han-Ying Liang","doi":"10.1016/j.jspi.2023.01.005","DOIUrl":"10.1016/j.jspi.2023.01.005","url":null,"abstract":"<div><p><span><span>Based on empirical likelihood method, we investigate </span>statistical inference<span> in partially linear single-index quantile regression<span> with high dimensional linear and single-index parameters when the observations are missing at random, which allows the response or </span></span></span>covariates<span> or response and covariates simultaneously missing. In particular, applying B-spline approximation to the unknown link function, we establish asymptotic normality<span><span> of bias-corrected empirical likelihood ratio function and maximum empirical likelihood estimators of the parameters. Variable selection is considered by using the SCAD penalty. Meanwhile, we propose a penalized empirical </span>likelihood ratio statistic to test hypothesis, and prove its asymptotically chi-square distribution under the null hypothesis. Also, simulation study and a real data analysis are conducted to evaluate the performance of the proposed methods.</span></span></p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47847570","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
Simultaneous inference for partial areas under receiver operating curves—With a view towards efficiency 接收机工作曲线下部分区域的同时推断——从效率的角度考虑
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.02.002
Maximilian Wechsung, Frank Konietschke
{"title":"Simultaneous inference for partial areas under receiver operating curves—With a view towards efficiency","authors":"Maximilian Wechsung,&nbsp;Frank Konietschke","doi":"10.1016/j.jspi.2023.02.002","DOIUrl":"10.1016/j.jspi.2023.02.002","url":null,"abstract":"<div><p>We propose new simultaneous inference methods for diagnostic trials with elaborate factorial designs. Instead of the commonly used total area under the receiver operating characteristic (ROC) curve, our parameters of interest are partial areas under ROC curve segments that represent clinically relevant biomarker cut-off values. We construct a nonparametric multiple contrast test for these parameters and show that it asymptotically controls the family-wise type one error rate. Finite sample properties of this test are investigated in a series of computer experiments. We provide empirical and theoretical evidence supporting the conjecture that statistical inference about partial areas under ROC curves is more efficient than inference about the total areas.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41265449","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: 2
Deterministic construction methods for uniform designs 均匀设计的确定性施工方法
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.02.001
Liangwei Qi, Ze Liu, Yongdao Zhou
{"title":"Deterministic construction methods for uniform designs","authors":"Liangwei Qi,&nbsp;Ze Liu,&nbsp;Yongdao Zhou","doi":"10.1016/j.jspi.2023.02.001","DOIUrl":"10.1016/j.jspi.2023.02.001","url":null,"abstract":"<div><p>Space-filling designs are useful for exploring the relationship between the response and factors, especially when the true model is unknown. The wrap-around <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-discrepancy is an important measure of the uniformity, and has often been used as a type of space-filling criterion. However, most obtained designs are generated through stochastic optimization algorithms, and cannot achieve the lower bound of the discrepancies and are only nearly uniform. Then deterministic construction methods for uniform designs are desired. This paper constructs uniform designs under the wrap-around <span><math><msub><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span><span><span><span>-discrepancy by generator matrices<span> of linear codes. Several requirements on the generator matrices, such as a necessary and sufficient condition for generating uniform designs, are derived. Based on these, two simple deterministic constructions for uniform designs are given. Some examples illustrate the effectiveness of them. Moreover, the resulting designs can be regarded as a generalization of good </span></span>lattice point sets, and also enjoy good </span>orthogonality.</span></p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43755449","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 stable sequential multiple test for Koopman–Darmois family Koopman-Darmois族的稳定序贯多重检验
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.01.006
Shuaiyu Chen, Yan Li, Xiaolong Pu, Dongdong Xiang
{"title":"A stable sequential multiple test for Koopman–Darmois family","authors":"Shuaiyu Chen,&nbsp;Yan Li,&nbsp;Xiaolong Pu,&nbsp;Dongdong Xiang","doi":"10.1016/j.jspi.2023.01.006","DOIUrl":"10.1016/j.jspi.2023.01.006","url":null,"abstract":"<div><p>Assuming that data are collected sequentially from multiple streams whose density functions belong to the Koopman–Darmois family, we implement simultaneous testing on multiple hypotheses with respect to parameters. To stabilize the expected sample sizes (ESSs) at all possible values of the true parameters, we intersect individual 2-SPRT plans and propose reasonable thresholds to balance stopping rules among streams. Under two types of constrained familywise error probabilities, we prove that our method has bounded maximum expected sample sizes (MESSs) and achieves asymptotic optimality in the sense of minimizing MESSs. Simulation results demonstrate the stability of our method, in the sense of achieving smaller MESSs than those of the baseline methods. We further apply our method to a real data set.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46515838","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 numerical method to obtain exact confidence intervals for likelihood-based parameter estimators 基于似然参数估计的精确置信区间的数值方法
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2022.12.006
Minsoo Jeong
{"title":"A numerical method to obtain exact confidence intervals for likelihood-based parameter estimators","authors":"Minsoo Jeong","doi":"10.1016/j.jspi.2022.12.006","DOIUrl":"10.1016/j.jspi.2022.12.006","url":null,"abstract":"<div><p>We propose a numerical method for obtaining exact confidence intervals<span> of likelihood-based parameter estimators for general multi-parameter models. Although the test inversion method provides exact confidence intervals, it is applicable only to single-parameter models. Our new method can be applied to general multi-parameter models without loss of accuracy, which is in sharp contrast to other multi-parameter extensions of the test inversion. Using Monte Carlo simulations<span>, we show that our method is feasible and provides correct coverage probabilities in finite samples.</span></span></p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42129679","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
A selective review of sufficient dimension reduction for multivariate response regression 多元响应回归充分降维的选择性评价
IF 0.9 4区 数学
Journal of Statistical Planning and Inference Pub Date : 2023-09-01 DOI: 10.1016/j.jspi.2023.02.003
Yuexiao Dong , Abdul-Nasah Soale , Michael D. Power
{"title":"A selective review of sufficient dimension reduction for multivariate response regression","authors":"Yuexiao Dong ,&nbsp;Abdul-Nasah Soale ,&nbsp;Michael D. Power","doi":"10.1016/j.jspi.2023.02.003","DOIUrl":"10.1016/j.jspi.2023.02.003","url":null,"abstract":"<div><p>We review sufficient dimension reduction (SDR) estimators with multivariate response in this paper. A wide range of SDR methods are characterized as inverse regression SDR estimators or forward regression SDR estimators. The inverse regression family includes pooled marginal estimators, projective resampling estimators, and distance-based estimators. Ordinary least squares, partial least squares, and semiparametric SDR estimators, on the other hand, are discussed as estimators from the forward regression family.</p></div>","PeriodicalId":50039,"journal":{"name":"Journal of Statistical Planning and Inference","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46320509","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: 2
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