发布求助
文献互助 智能选刊 最新文献

Journal of Nonparametric Statistics最新文献

筛选
英文 中文
Model fitting using partially ranked data 使用部分排序数据的模型拟合
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2023-02-19 DOI: 10.1080/10485252.2023.2176180
M. Alvo, XiuWen Duan
{"title":"Model fitting using partially ranked data","authors":"M. Alvo, XiuWen Duan","doi":"10.1080/10485252.2023.2176180","DOIUrl":"https://doi.org/10.1080/10485252.2023.2176180","url":null,"abstract":"The importance of models for complete ranking data is well-established in the literature. Partial rankings, on the other hand, arise naturally when the set of objects to be ranked is relatively large. Partial rankings give rise to classes of compatible order preserving complete rankings. In this article, we define an exponential model for complete rankings and calibrate it on the basis of a random sample of partial rankings data. We appeal to the EM algorithm. The approach is illustrated in some simulations and in real data.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"5 1","pages":"587 - 600"},"PeriodicalIF":1.2,"publicationDate":"2023-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80275203","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
Cramér-von-Mises tests for the distribution of the excess over a confidence level cramsamr -von- mises检验超额在一个置信水平上的分布
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2023-02-09 DOI: 10.1080/10485252.2023.2173958
D. Gaigall, Julian Gerstenberg
{"title":"Cramér-von-Mises tests for the distribution of the excess over a confidence level","authors":"D. Gaigall, Julian Gerstenberg","doi":"10.1080/10485252.2023.2173958","DOIUrl":"https://doi.org/10.1080/10485252.2023.2173958","url":null,"abstract":"The Cramér-von-Mises distance is applied to the distribution of the excess over a confidence level. Asymptotics of related statistics are investigated, and it is seen that the obtained limit distributions differ from the classical ones. For that reason, quantiles of the new limit distributions are given and new bootstrap techniques for approximation purposes are introduced and justified. The results motivate new one-sample goodness-of-fit tests for the distribution of the excess over a confidence level and a new confidence interval for the related fitting error. Simulation studies investigate size and power of the tests as well as coverage probabilities of the confidence interval in the finite sample case. A practice-oriented application of the Cramér-von-Mises tests is the determination of an appropriate confidence level for the fitting approach. The adoption of the idea to the well-known problem of threshold detection in the context of peaks over threshold modelling is sketched and illustrated by data examples.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"246 1","pages":"529 - 561"},"PeriodicalIF":1.2,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76184514","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
Asymptotic behaviour of the portmanteau tests in an integer-valued AR model 整数值AR模型中组合检验的渐近性态
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2023-02-07 DOI: 10.1080/10485252.2023.2175594
Jing Zhang, B. Li, Xiaohui Liu, Xinyue Wan
{"title":"Asymptotic behaviour of the portmanteau tests in an integer-valued AR model","authors":"Jing Zhang, B. Li, Xiaohui Liu, Xinyue Wan","doi":"10.1080/10485252.2023.2175594","DOIUrl":"https://doi.org/10.1080/10485252.2023.2175594","url":null,"abstract":"The portmanteau test has been popular for diagnostic checking in time series models. Asymptotic properties of portmanteau tests have been exhaustively studied for real-valued time series model though, similar results for integer-valued autoregressive (INAR) models are not well documented, nevertheless. In view of this, we investigate the asymptotic behaviour of the Box-Pierce and Ljung-Box portmanteau tests in an INAR model. It turns out that these tests are chi-squared distributed asymptotically under mild conditions regardless of the process being stable or nearly unstable.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"30 1","pages":"562 - 586"},"PeriodicalIF":1.2,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74280802","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
Choosing shape parameters for regression in reproducing kernel Hilbert space and variable selection 复现核希尔伯特空间中回归形状参数的选择及变量的选择
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2023-01-10 DOI: 10.1080/10485252.2023.2164890
Xin Tan, Yingcun Xia, Efang Kong
{"title":"Choosing shape parameters for regression in reproducing kernel Hilbert space and variable selection","authors":"Xin Tan, Yingcun Xia, Efang Kong","doi":"10.1080/10485252.2023.2164890","DOIUrl":"https://doi.org/10.1080/10485252.2023.2164890","url":null,"abstract":"The Gaussian radial basis function (RBF) is a widely used kernel function in kernel-based methods. The parameter in RBF, referred to as the shape parameter, plays an essential role in model fitting. In this paper, we propose a method to select the shape parameters for the general Gaussian RBF kernel. It can simultaneously serve for variable selection and regression function estimation. For the former, asymptotic consistency is established; for the latter, the estimation is as efficient as if the true or optimal shape parameters are known. Simulations and real examples are used to illustrate the method's performance of prediction by comparing it with other popular methods.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"70 1","pages":"514 - 528"},"PeriodicalIF":1.2,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86491419","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
Nonparametric inference for interval data using kernel methods 用核方法对区间数据进行非参数推理
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2023-01-03 DOI: 10.1080/10485252.2022.2160980
Hoyoung Park, J. Loh, Woncheol Jang
{"title":"Nonparametric inference for interval data using kernel methods","authors":"Hoyoung Park, J. Loh, Woncheol Jang","doi":"10.1080/10485252.2022.2160980","DOIUrl":"https://doi.org/10.1080/10485252.2022.2160980","url":null,"abstract":"ABSTRACT Symbolic data have become increasingly popular in the era of big data. In this paper, we consider density estimation and regression for interval-valued data, a special type of symbolic data, common in astronomy and official statistics. We propose kernel estimators with adaptive bandwidths to account for variability of each interval. Specifically, we derive cross-validation bandwidth selectors for density estimation and extend the Nadaraya–Watson estimator for regression with interval data. We assess the performance of the proposed methods in comparison with existing kernel methods by extensive simulation studies and real data analysis.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"21 1","pages":"455 - 473"},"PeriodicalIF":1.2,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81559954","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 axial symmetry by means of integrated rank scores 用综合等级分数检验轴对称性
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2022-12-26 DOI: 10.1080/10485252.2022.2159399
Š. Hudecová, M. Siman
{"title":"Testing axial symmetry by means of integrated rank scores","authors":"Š. Hudecová, M. Siman","doi":"10.1080/10485252.2022.2159399","DOIUrl":"https://doi.org/10.1080/10485252.2022.2159399","url":null,"abstract":"The article addresses the recently emerging inferential problem of testing axial symmetry up to a shift, which is useful even for testing certain hypotheses of exchangeability, independence, goodness-of-fit or equality of scale. In particular, it introduces a new test of axial symmetry based on integrated rank scores for directional quantile regression. The test outperforms existing competitors in terms of size, power, robustness, moment conditions or computational feasibility. All that is illustrated with a series of simulated examples.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"20 1","pages":"474 - 490"},"PeriodicalIF":1.2,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83047446","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
Maximum approximate Bernstein likelihood estimation in a two-sample semiparametric model 两样本半参数模型的最大近似Bernstein似然估计
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2022-12-21 DOI: 10.1080/10485252.2022.2158332
Zhong Guan
{"title":"Maximum approximate Bernstein likelihood estimation in a two-sample semiparametric model","authors":"Zhong Guan","doi":"10.1080/10485252.2022.2158332","DOIUrl":"https://doi.org/10.1080/10485252.2022.2158332","url":null,"abstract":"Maximum likelihood estimators are proposed for the parameters and the underlying densities in a semiparametric density ratio model in which the nonparametric baseline density is approximated by the Bernstein polynomial model. The EM algorithm is used to obtain the maximum approximate Bernstein likelihood estimates. The proposed method is illustrated by two real data from medical research and is shown by simulation to have better performance than the existing ones. Some asymptotic results are also presented and proved.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"7 1","pages":"437 - 453"},"PeriodicalIF":1.2,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87156439","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 POT second-order parameter for bias correction 估计偏置校正的POT二阶参数
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2022-12-16 DOI: 10.1080/10485252.2023.2226237
Nan Zou
{"title":"Estimating POT second-order parameter for bias correction","authors":"Nan Zou","doi":"10.1080/10485252.2023.2226237","DOIUrl":"https://doi.org/10.1080/10485252.2023.2226237","url":null,"abstract":"The stable tail dependence function provides a full characterization of the extremal dependence structures. Unfortunately, the estimation of the stable tail dependence function often suffers from significant bias, whose scale relates to the Peaks-Over-Threshold (POT) second-order parameter. For this second-order parameter, this paper introduces a penalized estimator that discourages it from being too close to zero. This paper then establishes this estimator's asymptotic consistency, uses it to correct the bias in the estimation of the stable tail dependence function, and illustrates its desirable empirical properties in the estimation of the extremal dependence structures.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"258 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77138146","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
Nonparametric inference about increasing odds rate distributions 关于增加的比值率分布的非参数推断
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2022-12-10 DOI: 10.1080/10485252.2023.2220050
T. Lando, Idir Arab, P. E. Oliveira
{"title":"Nonparametric inference about increasing odds rate distributions","authors":"T. Lando, Idir Arab, P. E. Oliveira","doi":"10.1080/10485252.2023.2220050","DOIUrl":"https://doi.org/10.1080/10485252.2023.2220050","url":null,"abstract":"To improve nonparametric estimates of lifetime distributions, we propose using the increasing odds rate (IOR) model as an alternative to other popular, but more restrictive, ``adverse ageing'' models, such as the increasing hazard rate one. This extends the scope of applicability of some methods for statistical inference under order restrictions, since the IOR model is compatible with heavy-tailed and bathtub distributions. We study a strongly uniformly consistent estimator of the cumulative distribution function of interest under the IOR constraint. Numerical evidence shows that this estimator often outperforms the classic empirical distribution function when the underlying model does belong to the IOR family. We also study two different tests, aimed at detecting deviations from the IOR property, and we establish their consistency. The performance of these tests is also evaluated through simulations.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"8 4 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78387434","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
Extended Glivenko–Cantelli theorem and L 1 strong consistency of innovation density estimator for time-varying semiparametric ARCH model 时变半参数ARCH模型创新密度估计的扩展Glivenko-Cantelli定理和L 1强相合性
IF 1.2 4区 数学
Journal of Nonparametric Statistics Pub Date : 2022-12-05 DOI: 10.1080/10485252.2022.2152813
Chen Zhong
{"title":"Extended Glivenko–Cantelli theorem and L 1 strong consistency of innovation density estimator for time-varying semiparametric ARCH model","authors":"Chen Zhong","doi":"10.1080/10485252.2022.2152813","DOIUrl":"https://doi.org/10.1080/10485252.2022.2152813","url":null,"abstract":"ABSTRACT This paper extends the classical Glivenko–Cantelli theorem for the empirical cumulative distribution function based on the innovations in the ARCH model with a slowly time-varying trend. In this semiparametric time-varying model, strong consistency for the innovation density estimator via kernel smoothing method is established, given that the trend and ARCH parameter estimators meet some mild conditions. Besides, the strong consistency for the Gaussian quasi maximum likelihood estimator (QMLE) in the time-varying ARCH parameter is established as well. Moreover, in terms of the existence of the trend in the data, two major nonparametric trend estimators, B-spline and kernel estimators, are shown to be appropriate for the strong consistency results.","PeriodicalId":50112,"journal":{"name":"Journal of Nonparametric Statistics","volume":"99 1","pages":"373 - 396"},"PeriodicalIF":1.2,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83605981","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
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：604180095
Book学术官方微信