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Varying-coefficient models and basis function approximations for the analysis of repeated measurements

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Cited by:

  1. Xuejun Ma & Yue Du & Jingli Wang, 2022. "Model detection and variable selection for mode varying coefficient model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 321-341, June.
  2. Ghosal, Rahul & Maity, Arnab, 2022. "A Score Based Test for Functional Linear Concurrent Regression," Econometrics and Statistics, Elsevier, vol. 21(C), pages 114-130.
  3. Yuan Yang & Ziyang Pan & Jian Kang & Chad Brummett & Yi Li, 2023. "Simultaneous selection and inference for varying coefficients with zero regions: a soft‐thresholding approach," Biometrics, The International Biometric Society, vol. 79(4), pages 3388-3401, December.
  4. Xiaochao Xia & Hao Ming, 2022. "A Flexibly Conditional Screening Approach via a Nonparametric Quantile Partial Correlation," Mathematics, MDPI, vol. 10(24), pages 1-32, December.
  5. Ming Xiong & Ao Yuan & Hong-Bin Fang & Colin O. Wu & Ming T. Tan, 2022. "Estimation and Hypothesis Test for Mean Curve with Functional Data by Reproducing Kernel Hilbert Space Methods, with Applications in Biostatistics," Mathematics, MDPI, vol. 10(23), pages 1-17, December.
  6. Agarwal, Gaurav & Tu, Wei & Sun, Ying & Kong, Linglong, 2022. "Flexible quantile contour estimation for multivariate functional data: Beyond convexity," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  7. Rahul Ghosal & Arnab Maity & Timothy Clark & Stefano B. Longo, 2020. "Variable selection in functional linear concurrent regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 565-587, June.
  8. Lian, Heng & Meng, Jie & Zhao, Kaifeng, 2015. "Spline estimator for simultaneous variable selection and constant coefficient identification in high-dimensional generalized varying-coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 81-103.
  9. Xing-cai Zhou & Jin-Guan Lin, 2014. "Empirical likelihood for varying-coefficient semiparametric mixed-effects errors-in-variables models with longitudinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 51-69, March.
  10. Hongmei Lin & Wenchao Xu & Riquan Zhang & Jianhong Shi & Yuedong Wang, 2017. "Multiple-index varying-coefficient models for longitudinal data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(11), pages 1960-1978, August.
  11. Huaihou Chen & Yuanjia Wang, 2011. "A Penalized Spline Approach to Functional Mixed Effects Model Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 861-870, September.
  12. Zhang, Xiaoke & Zhong, Qixian & Wang, Jane-Ling, 2020. "A new approach to varying-coefficient additive models with longitudinal covariates," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
  13. Lili Yue & Gaorong Li & Heng Lian, 2019. "Identification and estimation in quantile varying-coefficient models with unknown link function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1251-1275, December.
  14. Li, Jialiang & Xia, Yingcun & Palta, Mari & Shankar, Anoop, 2009. "Impact of unknown covariance structures in semiparametric models for longitudinal data: An application to Wisconsin diabetes data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4186-4197, October.
  15. Koki Momoki & Takuma Yoshida, 2024. "Hypothesis testing for varying coefficient models in tail index regression," Statistical Papers, Springer, vol. 65(6), pages 3821-3852, August.
  16. Y. Andriyana & I. Gijbels & A. Verhasselt, 2014. "P-splines quantile regression estimation in varying coefficient models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 153-194, March.
  17. Zhongnan Jin & Jie Min & Yili Hong & Pang Du & Qingyu Yang, 2024. "Multivariate Functional Clustering with Variable Selection and Application to Sensor Data from Engineering Systems," INFORMS Joural on Data Science, INFORMS, vol. 3(2), pages 203-218, October.
  18. Zhao, Weihua & Zhang, Riquan & Liu, Jicai & Hu, Hongchang, 2015. "Robust adaptive estimation for semivarying coefficient models," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 132-141.
  19. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.
  20. Peng, Heng & Xie, Chuanlong & Zhao, Jingxin, 2021. "Fast inference for semi-varying coefficient models via local averaging," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  21. Hu Yang & Chaohui Guo & Jing Lv, 2016. "Variable selection for generalized varying coefficient models with longitudinal data," Statistical Papers, Springer, vol. 57(1), pages 115-132, March.
  22. Lee, Jihui & Li, Gen & Wilson, James D., 2020. "Varying-coefficient models for dynamic networks," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  23. Jo Thori Lind, 2019. "Spurious weather effects," Journal of Regional Science, Wiley Blackwell, vol. 59(2), pages 322-354, March.
  24. Yijun Wang & Weiwei Wang, 2021. "Quantile estimation of semiparametric model with time-varying coefficients for panel count data," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-18, December.
  25. Jingyi Zhang & Xu Liu & Honglang Wang & Yuehua Cui, 2026. "Functional Varying-Index Coefficients Model for Dynamic Synergistic Gene–Environment Interactions," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 18(1), pages 111-130, March.
  26. Chaohui Guo & Hu Yang & Jing Lv, 2018. "Two step estimations for a single-index varying-coefficient model with longitudinal data," Statistical Papers, Springer, vol. 59(3), pages 957-983, September.
  27. Tang Qingguo & Cheng Longsheng, 2008. "M-estimation and B-spline approximation for varying coefficient models with longitudinal data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 611-625.
  28. Tian, Ruiqin & Xue, Liugen & Xu, Dengke, 2016. "Automatic variable selection for varying coefficient models with longitudinal data," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 84-90.
  29. Long Feng & Changliang Zou & Zhaojun Wang & Xianwu Wei & Bin Chen, 2015. "Robust spline-based variable selection in varying coefficient model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(1), pages 85-118, January.
  30. Bertho Tantular & Budi Nurani Ruchjana & Yudhie Andriyana & Anneleen Verhasselt, 2025. "Space-Time Varying Coefficient Model on Longitudinal Data of the Dengue Fever in Bandung City," Mathematics, MDPI, vol. 13(12), pages 1-13, June.
  31. Tian, Ruiqin & Xue, Liugen & Liu, Chunling, 2014. "Penalized quadratic inference functions for semiparametric varying coefficient partially linear models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 94-110.
  32. Chin-Tsang Chiang, 2005. "Comparisons between simultaneous and componentwise splines for varying coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(4), pages 637-653, December.
  33. Hao, Siteng & Lin, Shu-Chin & Wang, Jane-Ling & Zhong, Qixian, 2024. "Dynamic modeling for multivariate functional and longitudinal data," Journal of Econometrics, Elsevier, vol. 239(2).
  34. Shuping Jiang & Lan Xue, 2015. "Globally consistent model selection in semi-parametric additive coefficient models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(4), pages 532-551, December.
  35. Şentürk, Damla & Ghosh, Samiran & Nguyen, Danh V., 2014. "Exploratory time varying lagged regression: Modeling association of cognitive and functional trajectories with expected clinic visits in older adults," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 1-15.
  36. Zhao, Weihua & Jiang, Xuejun & Lian, Heng, 2018. "A principal varying-coefficient model for quantile regression: Joint variable selection and dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 269-280.
  37. Wang-Li Xu & Li-Xing Zhu, 2008. "Goodness-of-fit testing for varying-coefficient models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(2), pages 129-146, September.
  38. Wang, Qihua & Zhang, Riquan, 2009. "Statistical estimation in varying coefficient models with surrogate data and validation sampling," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2389-2405, November.
  39. Colin Wu & Xin Tian & Jarvis Yu, 2010. "Nonparametric estimation for time-varying transformation models with longitudinal data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 133-147.
  40. Jun Jin & Tiefeng Ma & Jiajia Dai & Shuangzhe Liu, 2021. "Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates," Computational Statistics, Springer, vol. 36(1), pages 541-575, March.
  41. Fang Lu & Li Peng & Guoliang Tian & Jing Yang, 2026. "Robust Bayesian variable selection for the quantile varying coefficient model," Computational Statistics, Springer, vol. 41(3), pages 1-31, April.
  42. Wangli Xu & Xu Guo, 2013. "Nonparametric checks for varying coefficient models with missing response at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(4), pages 459-482, May.
  43. Tang, Yanlin & Wang, Huixia Judy & Zhu, Zhongyi, 2013. "Variable selection in quantile varying coefficient models with longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 435-449.
  44. Sehee Kim & Donglin Zeng & Jeremy M. G. Taylor, 2017. "Joint partially linear model for longitudinal data with informative drop-outs," Biometrics, The International Biometric Society, vol. 73(1), pages 72-82, March.
  45. Qingming Zou & Zhongyi Zhu, 2014. "M-estimators for single-index model using B-spline," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 225-246, February.
  46. Zhang, Xiaoke & Wang, Jane-Ling, 2018. "Optimal weighting schemes for longitudinal and functional data," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 165-170.
  47. Tang Qingguo & Cheng Longsheng, 2012. "Componentwise B-spline estimation for varying coefficient models with longitudinal data," Statistical Papers, Springer, vol. 53(3), pages 629-652, August.
  48. Chen, Huaihou & Paik, Myunghee Cho & Dhamoon, Mandip S. & Moon, Yeseon Park & Willey, Joshua & Sacco, Ralph L. & Elkind, Mitchell S.V., 2012. "Semiparametric model for the dichotomized functional outcome after stroke: The Northern Manhattan Study," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2598-2608.
  49. Linjun Tang & Zhangong Zhou, 2015. "Weighted local linear CQR for varying-coefficient models with missing covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 583-604, September.
  50. Francesco Bravo, 2020. "Robust estimation and inference for general varying coefficient models with missing observations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 966-988, December.
  51. Zheng, Xueying & Xue, Lan & Qu, Annie, 2018. "Time-varying correlation structure estimation and local-feature detection for spatio-temporal data," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 221-239.
  52. Yuanqing Zhang & Chunrong Ai & Yaqin Feng, 2024. "Threshold effect in varying coefficient models with unknown heteroskedasticity," Computational Statistics, Springer, vol. 39(3), pages 1165-1181, May.
  53. Chin-Tsang Chiang, 2011. "A more flexible joint latent model for longitudinal and survival time data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 151-170, March.
  54. Qiu, Jia & Li, Degao & You, Jinhong, 2015. "SCAD-penalized regression for varying-coefficient models with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 100-118.
  55. Yang, Yiping & Li, Gaorong & Peng, Heng, 2014. "Empirical likelihood of varying coefficient errors-in-variables models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 1-18.
  56. Lian, Heng, 2015. "Quantile regression for dynamic partially linear varying coefficient time series models," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 49-66.
  57. Hui Ding & Mei Yao & Riquan Zhang, 2023. "A new estimation in functional linear concurrent model with covariate dependent and noise contamination," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 965-989, November.
  58. Li, Zaixing & Xu, Wangli & Zhu, Lixing, 2009. "Influence diagnostics and outlier tests for varying coefficient mixed models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2002-2017, October.
  59. Zhaoping Hong & Yuao Hu & Heng Lian, 2013. "Variable selection for high-dimensional varying coefficient partially linear models via nonconcave penalty," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(7), pages 887-908, October.
  60. Zhang, Shen & Zhao, Peixin & Li, Gaorong & Xu, Wangli, 2019. "Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 37-52.
  61. Weihua Zhao & Weiping Zhang & Heng Lian, 2020. "Marginal quantile regression for varying coefficient models with longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 213-234, February.
  62. Zhang, Riquan & Li, Guoying, 2007. "Averaged estimation of functional-coefficient regression models with different smoothing variables," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 455-461, February.
  63. Lichun Wang & Peng Lai & Heng Lian, 2013. "Polynomial spline estimation for generalized varying coefficient partially linear models with a diverging number of components," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(8), pages 1083-1103, November.
  64. Shireen Assaf & Stefano Campostrini & Cinzia Di Novi & Fang Xu & Carol Gotway Crawford, 2014. "Analyzing Disparities Trends for Health Care Insurance Coverage Among Non-Elderly Adults in the US: Evidence from the Behavioral Risk Factor Surveillance System, 1993-2009," Working Papers 2014: 14, Department of Economics, University of Venice "Ca' Foscari".
  65. Wang, Qihua & Xue, Liugen, 2011. "Statistical inference in partially-varying-coefficient single-index model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 1-19, January.
  66. Li, XiaoLi & You, JinHong, 2012. "Error covariance matrix correction based approach to functional coefficient regression models with generated covariates," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 263-281.
  67. Jeong, Seonghyun & Park, Minjae & Park, Taeyoung, 2017. "Analysis of binary longitudinal data with time-varying effects," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 145-153.
  68. Shujie Ma & Yanyuan Ma & Yanqing Wang & Eli S. Kravitz & Raymond J. Carroll, 2017. "A Semiparametric Single-Index Risk Score Across Populations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1648-1662, October.
  69. Stefan Stremersch & Aurélie Lemmens, 2009. "Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes," Marketing Science, INFORMS, vol. 28(4), pages 690-708, 07-08.
  70. Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.
  71. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
  72. Cho, Hyunkeun & Kim, Seonjin, 2017. "Model specification test in a semiparametric regression model for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 105-116.
  73. Zhou, Xing-cai & Xu, Ying-zhi & Lin, Jin-guan, 2017. "Wavelet estimation in varying coefficient models for censored dependent data," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 179-189.
  74. Kangning Wang & Wen Shan, 2021. "Copula and composite quantile regression-based estimating equations for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 441-455, June.
  75. Wang-Li Xu & Li-Xing Zhu, 2009. "A goodness-of-fit test for a varying-coefficients model in longitudinal studies," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(4), pages 427-440.
  76. Weihua Zhao & Riquan Zhang & Jicai Liu & Yazhao Lv, 2014. "Robust and efficient variable selection for semiparametric partially linear varying coefficient model based on modal regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 165-191, February.
  77. Lan Xue & Hua Liang, 2010. "Polynomial Spline Estimation for a Generalized Additive Coefficient Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 26-46, March.
  78. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  79. Ruosha Li & Xuelin Huang & Jorge Cortes, 2016. "Quantile residual life regression with longitudinal biomarker measurements for dynamic prediction," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(5), pages 755-773, November.
  80. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
  81. Badi H. Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: a Bayesian Semiparametric Model With Random Coefficients for a Panel of OECD Countries," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 217-253, Emerald Group Publishing Limited.
  82. Tsai, Guei-Feng & Qu, Annie, 2008. "Testing the significance of cell-cycle patterns in time-course microarray data using nonparametric quadratic inference functions," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1387-1398, January.
  83. Hidetoshi Matsui & Toshihiro Misumi, 2015. "Variable selection for varying-coefficient models with the sparse regularization," Computational Statistics, Springer, vol. 30(1), pages 43-55, March.
  84. Lijie Gu & Li Wang & Wolfgang Härdle & Lijian Yang, 2014. "A simultaneous confidence corridor for varying coefficient regression with sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 806-843, December.
  85. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
  86. Weihua Zhao & Jianbo Li & Heng Lian, 2018. "Adaptive varying-coefficient linear quantile model: a profiled estimating equations approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 553-582, June.
  87. Stremersch, S. & Lemmens, A., 2008. "Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes," ERIM Report Series Research in Management ERS-2008-026-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  88. Colin O. Wu & Kai F. Yu, 2002. "Nonparametric Varying-Coefficient Models for the Analysis of Longitudinal Data," International Statistical Review, International Statistical Institute, vol. 70(3), pages 373-393, December.
  89. M. Ahkim & I. Gijbels & A. Verhasselt, 2017. "Shape testing in varying coefficient models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 429-450, June.
  90. Liu, Lili & Lin, Lu, 2019. "Subgroup analysis for heterogeneous additive partially linear models and its application to car sales data," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 239-259.
  91. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
  92. Zhimeng Sun & Zhi Su & Jingyi Ma, 2014. "Focused vector information criterion model selection and model averaging regression with missing response," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(3), pages 415-432, April.
  93. Olga Klopp & Marianna Pensky, 2013. "Sparse High-dimensional Varying Coefficient Model : Non-asymptotic Minimax Study," Working Papers 2013-30, Center for Research in Economics and Statistics.
  94. Yixin Chen & Weixin Yao, 2017. "Unified Inference for Sparse and Dense Longitudinal Data in Time-varying Coefficient Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 268-284, March.
  95. Li, Gaorong & Zhu, Lixing & Xue, Liugen & Feng, Sanying, 2010. "Empirical likelihood inference in partially linear single-index models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 718-732, March.
  96. ChunJing Li & Yun Li & Xue Ding & XiaoGang Dong, 2020. "DGQR estimation for interval censored quantile regression with varying-coefficient models," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-17, November.
  97. Jason P. Estes & Danh V. Nguyen & Lorien S. Dalrymple & Yi Mu & Damla Şentürk, 2014. "Cardiovascular event risk dynamics over time in older patients on dialysis: A generalized multiple-index varying coefficient model approach," Biometrics, The International Biometric Society, vol. 70(3), pages 751-761, September.
  98. A. Antoniadis & I. Gijbels & S. Lambert-Lacroix, 2014. "Penalized estimation in additive varying coefficient models using grouped regularization," Statistical Papers, Springer, vol. 55(3), pages 727-750, August.
  99. Huilan Liu & Xiawei Zhang & Huaiqing Hu & Junjie Ma, 2024. "Analysis of the positive response data with the varying coefficient partially nonlinear multiplicative model," Statistical Papers, Springer, vol. 65(5), pages 3063-3092, July.
  100. Ye, Mao & Lu, Zhao-Hua & Li, Yimei & Song, Xinyuan, 2019. "Finite mixture of varying coefficient model: Estimation and component selection," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 452-474.
  101. Jing Lv & Chaohui Guo & Jibo Wu, 2019. "Smoothed empirical likelihood inference via the modified Cholesky decomposition for quantile varying coefficient models with longitudinal data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 999-1032, September.
  102. Zhao, Weihua & Lian, Heng, 2017. "Quantile index coefficient model with variable selection," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 40-58.
  103. Kangning Wang, 2018. "Variable selection for spatial semivarying coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(2), pages 323-351, April.
  104. Shireen Assaf & Stefano Campostrini & Cinzia Di Novi & Fang Xu & Carol Gotway Crawford, 2017. "Analyzing disparity trends for health care insurance coverage among non-elderly adults in the US: evidence from the Behavioral Risk Factor Surveillance System, 1993–2009," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(3), pages 387-398, April.
  105. Jun Jin & Tiefeng Ma & Jiajia Dai, 2021. "New efficient spline estimation for varying-coefficient models with two-step knot number selection," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 693-712, July.
  106. Lai, Peng & Li, Gaorong & Lian, Heng, 2013. "Quadratic inference functions for partially linear single-index models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 115-127.
  107. Jianqing Fan & Jiancheng Jiang, 2007. "Nonparametric inference with generalized likelihood ratio tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(3), pages 409-444, December.
  108. Byeong U. Park & Enno Mammen & Young K. Lee & Eun Ryung Lee, 2015. "Varying Coefficient Regression Models: A Review and New Developments," International Statistical Review, International Statistical Institute, vol. 83(1), pages 36-64, April.
  109. Han, Kyunghee & Park, Yeonjoo & Kim, Soo-Young, 2025. "Statistical inference for partially shape-constrained function-on-scalar linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 211(C).
  110. Chen, Yixin & Wang, Qin & Yao, Weixin, 2015. "Adaptive estimation for varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 17-31.
  111. Yiqiang Lu & Riquan Zhang, 2009. "Smoothing spline estimation of generalised varying-coefficient mixed model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 815-825.
  112. Jianbo Li & Minggao Gu & Tao Hu, 2012. "General partially linear varying-coefficient transformation models for ranking data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1475-1488, January.
  113. Wong, Heung & Zhang, Riquan & Ip, Wai-cheung & Li, Guoying, 2008. "Functional-coefficient partially linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 99(2), pages 278-305, February.
  114. Wu Cen & Zhong Ping-Shou & Cui Yuehua, 2018. "Additive varying-coefficient model for nonlinear gene-environment interactions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 17(2), pages 1-18, April.
  115. Zhang, Weiwei & Li, Gaorong & Xue, Liugen, 2011. "Profile inference on partially linear varying-coefficient errors-in-variables models under restricted condition," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 3027-3040, November.
  116. Peixin Zhao & Liugen Xue, 2011. "Variable selection for varying coefficient models with measurement errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(2), pages 231-245, September.
  117. You, Jinhong & Zhou, Haibo, 2007. "Two-stage efficient estimation of longitudinal nonparametric additive models," Statistics & Probability Letters, Elsevier, vol. 77(17), pages 1666-1675, November.
  118. repec:hum:wpaper:sfb649dp2014-002 is not listed on IDEAS
  119. Liu, Hefei & Song, Xinyuan & Zhang, Baoxue, 2022. "Varying-coefficient hidden Markov models with zero-effect regions," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
  120. Ying Chen & Su-Chun Cheng, 2004. "Mean Response Models of Repeated Measurements in Presence of Varying Effectiveness Onset," U.C. Berkeley Division of Biostatistics Working Paper Series 1148, Berkeley Electronic Press.
  121. Zhao, Peixin & Xue, Liugen, 2010. "Variable selection for semiparametric varying coefficient partially linear errors-in-variables models," Journal of Multivariate Analysis, Elsevier, vol. 101(8), pages 1872-1883, September.
  122. Lv, Shaogao & Fan, Zengyan & Lian, Heng & Suzuki, Taiji & Fukumizu, Kenji, 2020. "A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  123. Robert T. Krafty & Phyllis A. Gimotty & David Holtz & George Coukos & Wensheng Guo, 2008. "Varying Coefficient Model with Unknown Within-Subject Covariance for Analysis of Tumor Growth Curves," Biometrics, The International Biometric Society, vol. 64(4), pages 1023-1031, December.
  124. Wangli Xu & Lixing Zhu, 2013. "Testing the adequacy of varying coefficient models with missing responses at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(1), pages 53-69, January.
  125. Annie Qu & Runze Li, 2006. "Quadratic Inference Functions for Varying-Coefficient Models with Longitudinal Data," Biometrics, The International Biometric Society, vol. 62(2), pages 379-391, June.
  126. Kong, Dehan & Bondell, Howard D. & Wu, Yichao, 2015. "Domain selection for the varying coefficient model via local polynomial regression," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 236-250.
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