1
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Zhang J, Feng Z. A parametric hypothesis test for a global power law and local nonparametric trend model with multiplicative distortion measurement errors. COMMUN STAT-SIMUL C 2023. [DOI: 10.1080/03610918.2023.2182286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Zhenghui Feng
- School of Science, Harbin Institute of Technology, Shenzhen, Guangdong, China
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2
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Zhang J, Cui L. Exponential parametric distortion nonlinear measurement errors Models. COMMUN STAT-THEOR M 2022. [DOI: 10.1080/03610926.2022.2111526] [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 Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Leyi Cui
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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3
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Sevilimedu V, Yu L. Simulation extrapolation method for measurement error: A review. Stat Methods Med Res 2022; 31:1617-1636. [PMID: 35607297 PMCID: PMC10062410 DOI: 10.1177/09622802221102619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Measurement error is pervasive in statistics due to the non-availability of authentic data. The reasons for measurement error mainly relate to cost, convenience, and human error. Measurement error can result in non-negligible bias due to attenuated estimates, reduced power of statistical tests, and lower coverage probabilities of the coefficient estimators in a regression model. Several methods have been proposed to correct for measurement error, all of which can be grouped into two broad categories based on the underlying model-functional and structural. Functional models provide flexibility and robustness to estimators by placing minimal or no assumptions on the distribution of the mismeasured covariate or by treating them as a fixed entity, as opposed to a structural model which treats the underlying mismeasured covariates as random with a specified structure. The simulation extrapolation method is one method that is used for the partial correction of measurement error in both structural and functional models. Reviews of measurement error correction techniques are available in the literature. However, none of the previously conducted reviews has exclusively focused on simulation extrapolation and its application in continuous measurement error models, despite its widespread use and ease of application. We attempt to close this gap in the literature by highlighting its development over the past two and a half decades.
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Affiliation(s)
- Varadan Sevilimedu
- Department of Epidemiology and Biostatistics, 5803Memorial Sloan Kettering Cancer Center, Manhattan, New York, USA
| | - Lili Yu
- JPHCOPH, 123432Georgia Southern University, Statesboro, Georgia, USA
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4
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Zhang J. Partial linear additive distortion measurement errors models. COMMUN STAT-THEOR M 2022. [DOI: 10.1080/03610926.2022.2076126] [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 Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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5
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Zhu X, Zhang J, Yang Y. Additive distortion measurement errors regression models with exponential calibration. J STAT COMPUT SIM 2022. [DOI: 10.1080/00949655.2022.2055028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Xuehu Zhu
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China
| | - Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
| | - Yiping Yang
- College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, People's Republic of China
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6
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Zhang J. Nonparametric multiplicative distortion measurement errors models with bias reduction. COMMUN STAT-SIMUL C 2022. [DOI: 10.1080/03610918.2022.2061002] [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 Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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7
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Zhang J. Measurement errors models with exponential parametric multiplicative distortions. J STAT COMPUT SIM 2022. [DOI: 10.1080/00949655.2022.2037594] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
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8
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Ding H, Zhang R, Zhu H. New estimation for heteroscedastic single-index measurement error models. J Nonparametr Stat 2022. [DOI: 10.1080/10485252.2021.2025238] [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)
- Hui Ding
- School of Economics, Nanjing University of Finance and Economics, Nanjing, People's Republic of China
| | - Riquan Zhang
- School of Statistics, Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, East China Normal University, Shanghai, People's Republic of China
| | - Hanbing Zhu
- School of Statistics, Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, East China Normal University, Shanghai, People's Republic of China
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9
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Zhang J, Yang B, Feng Z. Estimation of correlation coefficient under a linear multiplicative distortion measurement errors model. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.2004421] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Baojun Yang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Zhenghui Feng
- School of Economics, and Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China
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10
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Zhang J. Nonlinear multiplicative distortion regression models with second-order estimation. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.2001656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China
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11
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Zhang J, Gai Y. Linear regression models with general distortion measurement errors. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2019.1622723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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
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12
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Feng Z, Zhang J, Yang B. Average derivation estimation with multiplicative distortion measurement errors. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1992635] [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)
- Zhenghui Feng
- School of Economics, and Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China
| | - Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Baojun Yang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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13
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Huang Z, Jiang Z, Li J. Statistical inference for a single-index varying coefficient model with measurement errors in all covariates. J STAT COMPUT SIM 2021. [DOI: 10.1080/00949655.2021.1984486] [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
| | - Zhiqiang Jiang
- School of Science, Nanjing University of Science and Technology, Nanjing, People's Republic of China
| | - Jing Li
- School of Science, Nanjing University of Science and Technology, Nanjing, People's Republic of China
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14
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Zhang J, Yang Y. Modal linear regression models with additive distortion measurement errors. J STAT COMPUT SIM 2021. [DOI: 10.1080/00949655.2021.1979000] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
| | - Yiping Yang
- College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, People's Republic of China
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15
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Zhang J, Lin B. Estimation of correlation coefficient with general distortion measurement errors. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1963453] [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)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Bingqing Lin
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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16
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Zhang J, Li G, Yang Y. Modal linear regression models with multiplicative distortion measurement errors. Stat Anal Data Min 2021. [DOI: 10.1002/sam.11541] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics Shenzhen University Shenzhen China
| | - Gaorong Li
- School of Statistics Beijing Normal University Beijing China
| | - Yiping Yang
- College of Mathematics and Statistics Chongqing Technology and Business University Chongqing China
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18
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Wu S, Chen Y, Li Z, Li J, Zhao F, Su X. Towards multi-label classification: Next step of machine learning for microbiome research. Comput Struct Biotechnol J 2021; 19:2742-2749. [PMID: 34093989 PMCID: PMC8131981 DOI: 10.1016/j.csbj.2021.04.054] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 11/22/2022] Open
Abstract
Machine learning (ML) has been widely used in microbiome research for biomarker selection and disease prediction. By training microbial profiles of samples from patients and healthy controls, ML classifiers constructs data models by community features that highly correlated with the target diseases, so as to determine the status of new samples. To clearly understand the host-microbe interaction of specific diseases, previous studies always focused on well-designed cohorts, in which each sample was exactly labeled by a single status type. However, in fact an individual may be associated with multiple diseases simultaneously, which introduce additional variations on microbial patterns that interferes the status detection. More importantly, comorbidities or complications can be missed by regular ML models, limiting the practical application of microbiome techniques. In this review, we summarize the typical ML approaches of single-label classification for microbiome research, and demonstrate their limitations in multi-label disease detection using a real dataset. Then we prospect a further step of ML towards multi-label classification that potentially solves the aforementioned problem, including a series of promising strategies and key technical issues for applying multi-label classification in microbiome-based studies.
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Affiliation(s)
- Shunyao Wu
- College of Computer Science and Technology, Qingdao University, Qingdao, Shandong 266071, China
| | - Yuzhu Chen
- College of Computer Science and Technology, Qingdao University, Qingdao, Shandong 266071, China
| | - Zhiruo Li
- School of Mathematics and Statistics, Qingdao University, Qingdao, Shandong 266071, China
| | - Jian Li
- College of Computer Science and Technology, Qingdao University, Qingdao, Shandong 266071, China
| | - Fengyang Zhao
- College of Computer Science and Technology, Qingdao University, Qingdao, Shandong 266071, China
| | - Xiaoquan Su
- College of Computer Science and Technology, Qingdao University, Qingdao, Shandong 266071, China
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19
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Huang Z, Lou W. Statistical inferences for single-index models with measurement errors. J Appl Stat 2021; 48:1033-1052. [DOI: 10.1080/02664763.2020.1754358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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
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20
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Zhang J, Cui X. Logarithmic calibration for nonparametric multiplicative distortion measurement errors models. J STAT COMPUT SIM 2021. [DOI: 10.1080/00949655.2021.1904240] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
| | - Xia Cui
- School of Economics and Statistics, Guangzhou University, Guangzhou, People's Republic of China
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21
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Zhang J. Model checking for multiplicative linear regression models with mixed estimators. STAT NEERL 2021. [DOI: 10.1111/stan.12239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics Shenzhen University Shenzhen China
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22
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Zhang J, Chen A, Wei Z. Kernel density estimation for multiplicative distortion measurement regression models. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1890122] [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)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Aixian Chen
- School of Economics and Statistics, Guangzhou University, Guangzhou, China
| | - Zhenghong Wei
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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23
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Zhang J, Xu Z, Wei Z. Absolute logarithmic calibration for correlation coefficient with multiplicative distortion. COMMUN STAT-SIMUL C 2020. [DOI: 10.1080/03610918.2020.1859541] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Zhuoer Xu
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
- College of Management, Shenzhen University, Shenzhen, China
| | - Zhenghong Wei
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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24
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Zhang J, Zhou Y. Calibration procedures for linear regression models with multiplicative distortion measurement errors. BRAZ J PROBAB STAT 2020. [DOI: 10.1214/19-bjps451] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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25
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Zhou H, Zhang J. General least product relative error estimation for multiplicative regression models with or without multiplicative distortion measurement errors. COMMUN STAT-SIMUL C 2020. [DOI: 10.1080/03610918.2020.1801731] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Huili Zhou
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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26
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Zhang J, Feng S, Gai Y. Partial index additive models with additive distortion measurement errors. COMMUN STAT-SIMUL C 2020. [DOI: 10.1080/03610918.2020.1757712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Sanying Feng
- School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, China
| | - Yujie Gai
- School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China
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27
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Gai Y, Zhang J. Detection of the symmetry of model errors for partial linear single-index models. COMMUN STAT-SIMUL C 2020. [DOI: 10.1080/03610918.2020.1752381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Yujie Gai
- School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China
| | - Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
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28
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Zhang J, Yang Y, Feng S, Wei Z. Logarithmic calibration for partial linear models with multiplicative distortion measurement errors. J STAT COMPUT SIM 2020. [DOI: 10.1080/00949655.2020.1750614] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
| | - Yiping Yang
- College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, People's Republic of China
| | - Sanying Feng
- School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, People's Republic of China
| | - Zhenghong Wei
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, People's Republic of China
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29
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Zhang J, Lin B, Feng Z. Conditional absolute mean calibration for partial linear multiplicative distortion measurement errors models. Comput Stat Data Anal 2020. [DOI: 10.1016/j.csda.2019.06.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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30
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Zhang J, Gai Y. Correlation coefficient-based measure for checking symmetry or asymmetry of a continuous variable with additive distortion. COMMUN STAT-SIMUL C 2019. [DOI: 10.1080/03610918.2019.1699573] [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)
- Jun Zhang
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Yujie Gai
- School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China
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31
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Semiparametric estimation for cure survival model with left-truncated and right-censored data and covariate measurement error. Stat Probab Lett 2019. [DOI: 10.1016/j.spl.2019.06.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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32
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Zhang J, Xu W, Gai Y. Multiplicative distortion measurement errors linear models with general moment identifiability condition. J STAT COMPUT SIM 2019. [DOI: 10.1080/00949655.2019.1678624] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen, People's Republic of China
| | - Wangli Xu
- Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, People's Republic of China
| | - Yujie Gai
- School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, People's Republic of China
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Affiliation(s)
- Jun Zhang
- Department of Statistics, College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen-Hong Kong Joint Research Center for Applied Statistical Sciences, Shenzhen University, Shenzhen, China
| | - Yujie Gai
- Department of Statistics and Mathematics, School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China
| | - Feng Li
- Department of Statistics, School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, China
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34
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Estimation and variable selection for partial linear single-index distortion measurement errors models. Stat Pap (Berl) 2019. [DOI: 10.1007/s00362-019-01119-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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35
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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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36
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Feng Z, Gai Y, Zhang J. Correlation curve estimation for multiplicative distortion measurement errors data. J Nonparametr Stat 2019. [DOI: 10.1080/10485252.2019.1580708] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Zhenghui Feng
- School of Economics and the Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, 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
| | - Jun Zhang
- College of Mathematics and Statistics, Institute of Statistical Sciences, Shenzhen University, Shenzhen-Hong Kong Joint Research Center for Applied Statistical Sciences, Shenzhen, China
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