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Ng HM, Jiang B, Wong KY. Penalized estimation of a class of single-index varying-coefficient models for integrative genomic analysis. Biom J 2023; 65:e2100139. [PMID: 35837982 DOI: 10.1002/bimj.202100139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 04/15/2022] [Accepted: 05/27/2022] [Indexed: 01/17/2023]
Abstract
Recent technological advances have made it possible to collect high-dimensional genomic data along with clinical data on a large number of subjects. In the studies of chronic diseases such as cancer, it is of great interest to integrate clinical and genomic data to build a comprehensive understanding of the disease mechanisms. Despite extensive studies on integrative analysis, it remains an ongoing challenge to model the interaction effects between clinical and genomic variables, due to high dimensionality of the data and heterogeneity across data types. In this paper, we propose an integrative approach that models interaction effects using a single-index varying-coefficient model, where the effects of genomic features can be modified by clinical variables. We propose a penalized approach for separate selection of main and interaction effects. Notably, the proposed methods can be applied to right-censored survival outcomes based on a Cox proportional hazards model. We demonstrate the advantages of the proposed methods through extensive simulation studies and provide applications to a motivating cancer genomic study.
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Affiliation(s)
- Hoi Min Ng
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
| | - Binyan Jiang
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
| | - Kin Yau Wong
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong
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2
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Robust MAVE for single-index varying-coefficient models. J Korean Stat Soc 2022. [DOI: 10.1007/s42952-022-00187-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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3
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Sun J, Liu W, Yang J, Fang J. Local Walsh-average regression for single index varying coefficient models. COMMUN STAT-THEOR M 2022. [DOI: 10.1080/03610926.2022.2060514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Jun Sun
- Key Laboratory of Computing and Stochastic Mathematics (Ministry of Education), School of Mathematics and Statistics, Hunan Normal University, Changsha, P.R. China
| | - Wanrong Liu
- Key Laboratory of Computing and Stochastic Mathematics (Ministry of Education), School of Mathematics and Statistics, Hunan Normal University, Changsha, P.R. China
| | - Jing Yang
- Key Laboratory of Computing and Stochastic Mathematics (Ministry of Education), School of Mathematics and Statistics, Hunan Normal University, Changsha, P.R. China
| | - Jianglin Fang
- School of Computational Science and Electronics, Hunan Institute of Engineering, Xiangtan, P.R. China
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4
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Zhao Y, Feng S. Robust estimation for partial linear single-index models. J Nonparametr Stat 2022. [DOI: 10.1080/10485252.2022.2027411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Yang Zhao
- Department of Mathematics, Nanchang University, Nanchang, People's Republic of China
| | - Sanying Feng
- School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, People's Republic of China
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5
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Huang Z, Lou W, Meng S. Statistical estimation for single-index varying-coefficient models with multiplicative distortion measurement errors. STATISTICS-ABINGDON 2021. [DOI: 10.1080/02331888.2021.1980794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Zhensheng Huang
- School of Science, Nanjing University of Science and Technology, Nanjing, People's Republic of China
| | - Wen Lou
- School of Science, Nanjing University of Science and Technology, Nanjing, People's Republic of China
| | - Shuyu Meng
- School of Science, Nanjing University of Science and Technology, Nanjing, People's Republic of China
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Sun W, Bindele HF, Abebe A, Correia HE. Robust functional coefficient selection for the single-index varying coefficients regression model. J STAT COMPUT SIM 2021. [DOI: 10.1080/00949655.2020.1867548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- W. Sun
- Department of Mathematics and Statistics, Auburn University, Auburn, AL, USA
| | - H. F. Bindele
- Dept. of Mathematics and Statistics, University of South Alabama, Mobile, AL, USA
| | - A. Abebe
- Department of Mathematics and Statistics, Auburn University, Auburn, AL, USA
| | - H. E. Correia
- Department of Biostatistics, Harvard University, Boston, MA, USA
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Semiparametric model selection for identification of environmental covariates related to adult groundfish catches and weights. Sci Rep 2021; 11:9949. [PMID: 33976295 PMCID: PMC8113536 DOI: 10.1038/s41598-021-89398-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 04/21/2021] [Indexed: 11/12/2022] Open
Abstract
Ecologists and fisheries managers are interested in monitoring economically important marine fish species and using this data to inform management strategies. Determining environmental factors that best predict changes in these populations, particularly under rapid climate change, are a priority. I illustrate the application of the least squares-based spline estimation and group LASSO (LSSGLASSO) procedure for selection of coefficient functions in single index varying coefficient models (SIVCMs) on an ecological data set that includes spatiotemporal environmental covariates suspected to play a role in the catches and weights of six groundfish species. Temporal trends in variable selection were apparent, though the selection of variables was largely unrelated to common North Pacific climate indices. These results indicate that the strength of an environmental variable’s effect on a groundfish population may change over time, and not necessarily in-step with known low-frequency patterns of ocean-climate variability commonly attributable to large-scale regime shifts in the North Pacific. My application of the LSSGLASSO procedure for SIVCMs to deep water species using environmental data from various sources illustrates how variable selection with a flexible model structure can produce informative inference for remote and hard-to-reach animal populations.
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Zhao Y, Xue L, Zhang J, Liu J. Single-index varying-coefficient models with missing covariates at random. COMMUN STAT-SIMUL C 2020. [DOI: 10.1080/03610918.2020.1833216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Yang Zhao
- School of Science, Nanchang University, Nanchang, China
| | - Liugen Xue
- Faculty of Science, Beijing University of Technology, Beijing, China
| | - Jinghua Zhang
- Faculty of Science, Beijing University of Technology, Beijing, China
| | - Juanfang Liu
- College of Mathematics and Information Science, Henan Normal University, Xinxiang, China
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Wang T, Wang L, Zhou X. Estimation in single-index varying-coefficient panel data model. COMMUN STAT-THEOR M 2020. [DOI: 10.1080/03610926.2020.1804589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Tonghui Wang
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
| | - Liming Wang
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
| | - Xian Zhou
- Department of Applied Finance and Actuarial Studies, Macquarie University, North Ryde, New South Wales, Australia
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Lai P, Wang F, Zhu T, Zhang Q. Model identification and selection for single-index varying-coefficient models. ANN I STAT MATH 2020. [DOI: 10.1007/s10463-020-00757-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Zhao Y, Xue L, Feng S. Estimation for a partially linear single-index varying-coefficient model. COMMUN STAT-SIMUL C 2019. [DOI: 10.1080/03610918.2019.1680691] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Yang Zhao
- School of Science, Nanchang University, Nanchang, China
- College of Applied Sciences, Beijing University of Technology, Beijing, China
| | - Liugen Xue
- College of Applied Sciences, Beijing University of Technology, Beijing, China
| | - Sanying Feng
- School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, China
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Zhang J, Gai Y, Lin B, Zhu X. Nonlinear regression models with single‐index heteroscedasticity. STAT NEERL 2019. [DOI: 10.1111/stan.12170] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical SciencesShenzhen University Shenzhen China
| | - Yujie Gai
- School of Statistics and MathematicsCentral University of Finance and Economics Beijing China
| | - Bingqing Lin
- College of Mathematics and Statistics, Institute of Statistical SciencesShenzhen University Shenzhen China
| | - Xuehu Zhu
- School of Mathematics and StatisticsXi'an Jiaotong University Xi'an China
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Zhang J, Gai Y, Lin B. Detection of marginal heteroscedasticity for partial linear single-index models. COMMUN STAT-SIMUL C 2019. [DOI: 10.1080/03610918.2019.1565585] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China
| | - Yujie Gai
- School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China
- Department of Biostatistics School of Public Health, University of Texas at Houston, Houston, TX, USA
| | - Bingqing Lin
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China
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Efficient estimation and variable selection for partially linear single-index-coefficient regression models. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2019. [DOI: 10.29220/csam.2019.26.1.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Zhang J, Niu C, Lu T, Wei Z. Estimation of the error distribution function for partial linear single-index models. COMMUN STAT-SIMUL C 2018. [DOI: 10.1080/03610918.2018.1468461] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China
| | - Cuizhen Niu
- School of Statistics, Beijing Normal University, Beijing, China
| | - Tao Lu
- Department of Mathematics and Statistics, University of Nevada, Reno, NV, USA
| | - Zhenghong Wei
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China
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18
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Two step estimations for a single-index varying-coefficient model with longitudinal data. Stat Pap (Berl) 2016. [DOI: 10.1007/s00362-016-0798-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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19
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Lai P, Zhang Q, Lian H, Wang Q. Efficient estimation for the heteroscedastic single-index varying coefficient models. Stat Probab Lett 2016. [DOI: 10.1016/j.spl.2015.12.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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