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A New Regression Model: Modal Linear Regression

Citations

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Cited by:

  1. Wang, Kangning & Li, Shaomin & Sun, Xiaofei & Lin, Lu, 2019. "Modal regression statistical inference for longitudinal data semivarying coefficient models: Generalized estimating equations, empirical likelihood and variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 257-276.
  2. Wang, Kangning & Li, Shaomin, 2021. "Robust distributed modal regression for massive data," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
  3. Gordon C. R. Kemp & Paulo M. D. C. Parente & J. M. C. Santos Silva, 2020. "Dynamic Vector Mode Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 647-661, July.
  4. Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
  5. Xin Jing & Jin Seo Cho, 2023. "Forecasting the Confirmed COVID-19 Cases Using Modal Regression," Working papers 2023rwp-217, Yonsei University, Yonsei Economics Research Institute.
  6. Jales, Hugo & Jiang, Boqian & Rosenthal, Stuart S., 2023. "JUE Insight: Using the mode to test for selection in city size wage premia," Journal of Urban Economics, Elsevier, vol. 133(C).
  7. Aman Ullah & Tao Wang & Weixin Yao, 2021. "Modal regression for fixed effects panel data," Empirical Economics, Springer, vol. 60(1), pages 261-308, January.
  8. Yen-Chi Chen, 2017. "Modal Regression using Kernel Density Estimation: a Review," Papers 1710.07004, arXiv.org, revised Dec 2017.
  9. Xin Jing & Jin Seo Cho, 2025. "Forecasting the Confirmed COVID‐19 Cases Using Modal Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1578-1601, July.
  10. Lianqiang Yang & Wanli Yuan & Shijie Wang, 2025. "Modal regression models based on B-splines," Computational Statistics, Springer, vol. 40(1), pages 225-248, January.
  11. Evon M. Abu-Taieh & Issam AlHadid & Ra’ed Masa’deh & Rami S. Alkhawaldeh & Sufian Khwaldeh & Ala’aldin Alrowwad, 2022. "Factors Affecting the Use of Social Networks and Its Effect on Anxiety and Depression among Parents and Their Children: Predictors Using ML, SEM and Extended TAM," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
  12. Eduardo Schirmer Finn & Eduardo Horta, 2024. "Convolution Mode Regression," Papers 2412.05736, arXiv.org.
  13. Ullah, Aman & Wang, Tao & Yao, Weixin, 2023. "Semiparametric partially linear varying coefficient modal regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 1001-1026.
  14. Shaomin Li & Kangning Wang & Yong Xu, 2023. "Robust estimation for nonrandomly distributed data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 493-509, June.
  15. Hu Yang & Ning Li & Jing Yang, 2020. "A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates," Statistical Papers, Springer, vol. 61(5), pages 1911-1937, October.
  16. Hongpeng Yuan & Sijia Xiang & Weixin Yao, 2024. "A new bandwidth selection method for nonparametric modal regression based on generalized hyperbolic distributions," Computational Statistics, Springer, vol. 39(4), pages 1729-1746, June.
  17. Yunlu Jiang & Guo-Liang Tian & Yu Fei, 2019. "A robust and efficient estimation method for partially nonlinear models via a new MM algorithm," Statistical Papers, Springer, vol. 60(6), pages 2063-2085, December.
  18. Tao Wang, 2024. "Non‐parametric Estimator for Conditional Mode with Parametric Features," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(1), pages 44-73, February.
  19. Yang, Jing & Tian, Guoliang & Lu, Fang & Lu, Xuewen, 2020. "Single-index modal regression via outer product gradients," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  20. Katarzyna Lukiewska, 2022. "Impact of Labor Productivity on the Export Performance of the Food Industry in EU Member States," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 74-83.
  21. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear modal regression for dependent data with application for predicting COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1424-1453, July.
  22. Yue Chao & Lei Huang & Xuejun Ma & Jiajun Sun, 2024. "Optimal subsampling for modal regression in massive data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 87(4), pages 379-409, May.
  23. Francesco Dotto & Alessio Farcomeni & Luis Angel García-Escudero & Agustín Mayo-Iscar, 2017. "A fuzzy approach to robust regression clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 691-710, December.
  24. Grace Isidor Temba & Pendo Shukrani Kasoga & Chirongo Moses Keregero, 2024. "Impact of the quality of credit risk management practices on financial performance of commercial banks in Tanzania," SN Business & Economics, Springer, vol. 4(3), pages 1-29, March.
  25. Zhe Sun & Yundong Tu, 2024. "Factors in Fashion: Factor Analysis towards the Mode," Papers 2409.19287, arXiv.org.
  26. repec:esx:essedp:761 is not listed on IDEAS
  27. Shi, Jianhong & Zhang, Yujing & Yu, Ping & Song, Weixing, 2021. "SIMEX estimation in parametric modal regression with measurement error," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  28. Tao Wang, 2024. "Nonlinear kernel mode‐based regression for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(2), pages 189-213, March.
  29. Liu, Qingyang & Huang, Xianzheng & Bai, Ray, 2024. "Bayesian modal regression based on mixture distributions," Computational Statistics & Data Analysis, Elsevier, vol. 199(C).
  30. Andrés Muñoz & Daniela Rodriguez, 2023. "Robust estimation in partially nonlinear models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1407-1437, December.
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