Sankhya. Series B. [Methodological.]最新文献

Mediation Analysis using Semi-parametric Shape-Restricted Regression with Applications. 半参数形状限制回归的中介分析及其应用。

Sankhya. Series B. [Methodological.] Pub Date : 2024-11-01 Epub Date: 2024-07-02 DOI: 10.1007/s13571-024-00336-w

Qing Yin, Jong-Hyeon Jeong, Xu Qin, Shyamal D Peddada, Jennifer J Adibi

引用次数: 0

A Blockwise Consistency Method for Parameter Estimation of Complex Models. 复杂模型参数估计的顺时针一致性方法

Sankhya. Series B. [Methodological.] Pub Date : 2018-12-01 Epub Date: 2019-02-07 DOI: 10.1007/s13571-018-0183-0

Runmin Shi, Faming Liang, Qifan Song, Ye Luo, Malay Ghosh

{"title":"A Blockwise Consistency Method for Parameter Estimation of Complex Models.","authors":"Runmin Shi, Faming Liang, Qifan Song, Ye Luo, Malay Ghosh","doi":"10.1007/s13571-018-0183-0","DOIUrl":"10.1007/s13571-018-0183-0","url":null,"abstract":"The drastic improvement in data collection and acquisition technologies has enabled scientists to collect a great amount of data. With the growing dataset size, typically comes a growing complexity of data structures and of complex models to account for the data structures. How to estimate the parameters of complex models has put a great challenge on current statistical methods. This paper proposes a blockwise consistency approach as a potential solution to the problem, which works by iteratively finding consistent estimates for each block of parameters conditional on the current estimates of the parameters in other blocks. The blockwise consistency approach decomposes the high-dimensional parameter estimation problem into a series of lower-dimensional parameter estimation problems, which often have much simpler structures than the original problem and thus can be easily solved. Moreover, under the framework provided by the blockwise consistency approach, a variety of methods, such as Bayesian and frequentist methods, can be jointly used to achieve a consistent estimator for the original high-dimensional complex model. The blockwise consistency approach is illustrated using two high-dimensional problems, variable selection and multivariate regression. The results of both problems show that the blockwise consistency approach can provide drastic improvements over the existing methods. Extension of the blockwise consistency approach to many other complex models is straightforward.","PeriodicalId":85487,"journal":{"name":"Sankhya. Series B. [Methodological.]","volume":"80 1 Suppl","pages":"179-223"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8026010/pdf/nihms-996656.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25583525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NONPARAMETRIC BENCHMARK ANALYSIS IN RISK ASSESSMENT: A COMPARATIVE STUDY BY SIMULATION AND DATA ANALYSIS. 风险评估中的非参数基准分析:模拟与数据分析的比较研究。

Sankhya. Series B. [Methodological.] Pub Date : 2011-05-01 DOI: 10.1007/s13571-011-0019-7

Rabi Bhattacharya, Lizhen Lin

引用次数: 16

Rejoinder on Discussion of: What's So Special About Semiparametric Methods? 半参数方法有什么特别之处?

Sankhya. Series B. [Methodological.] Pub Date : 2009-08-01

Michael R Kosorok

引用次数: 0

What's So Special About Semiparametric Methods? 半参数方法有什么特别之处?

Sankhya. Series B. [Methodological.] Pub Date : 2009-08-01

Michael R Kosorok

引用次数: 0

Statistical inference under order restrictions in analysis of covariance using a modified restricted maximum likelihood estimator. 用改进的限制极大似然估计量进行协方差分析中序约束下的统计推断。

Sankhya. Series B. [Methodological.] Pub Date : 2009-01-01

Joshua Betcher, Shyamal D Peddada

{"title":"Statistical inference under order restrictions in analysis of covariance using a modified restricted maximum likelihood estimator.","authors":"Joshua Betcher, Shyamal D Peddada","doi":"","DOIUrl":"","url":null,"abstract":"In this article we introduce a new procedure for estimating population parameters under inequality constraints (known as order restrictions) when the unrestricted maximum liklelihood estimator (UMLE) is multivariate normally distributed with a known covariance matrix. Furthermore, a Dunnett-type test procedure along with the corresponding simultaneous confidence intervals are proposed for drawing inferences on elementary contrasts of population parameters under order restrictions. The proposed methodology is motivated by estimation and testing problems encountered in the analysis of covariance models. It is well-known that the restricted maximum likelihood estimator (RMLE) may perform poorly under certain conditions in terms of quadratic loss. For example, when the UMLE is distributed according to multivariate normal distribution with means satisfying simple tree order restriction and the dimension of the population mean vector is large. We investigate the performance of the proposed estimator analytically as well as using computer simulations and discover that the proposed method does not fail in the situations where RMLE fails. We illustrate the proposed methodology by re-analyzing a recently published rat uterotrophic bioassay data.","PeriodicalId":85487,"journal":{"name":"Sankhya. Series B. [Methodological.]","volume":"71 1","pages":"79-96"},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2955899/pdf/nihms202681.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29359373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Some analytical models to estimate maternal age at birth using age-specific fertility rates. 使用特定年龄生育率估计产妇出生年龄的一些分析模型。

Sankhya. Series B. [Methodological.] Pub Date : 1995-01-01

A Pandey, C M Suchindran