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Constrained linear regression models for symbolic interval-valued variables

Citations

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Cited by:

  1. Paolo Giordani, 2015. "Lasso-constrained regression analysis for interval-valued data," 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. 9(1), pages 5-19, March.
  2. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
  3. Lin, Wei & González-Rivera, Gloria, 2016. "Interval-valued time series models: Estimation based on order statistics exploring the Agriculture Marketing Service data," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 694-711.
  4. Antonio Irpino & Rosanna Verde, 2015. "Linear regression for numeric symbolic variables: a least squares approach based on Wasserstein Distance," 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. 9(1), pages 81-106, March.
  5. Wagner J. F. Silva & Renata M. C. R. Souza & F. J. A. Cysneiros, 2022. "Bivariate elliptical regression for modeling interval-valued data," Computational Statistics, Springer, vol. 37(4), pages 2003-2028, September.
  6. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt’s exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759.
  7. Eufr�sio de A. Lima Neto & Ulisses U. dos Anjos, 2015. "Regression model for interval-valued variables based on copulas," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(9), pages 2010-2029, September.
  8. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
  9. Antonio Calcagnì & Luigi Lombardi & Lorenzo Avanzi & Eduardo Pascali, 2020. "Multiple mediation analysis for interval-valued data," Statistical Papers, Springer, vol. 61(1), pages 347-369, February.
  10. Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
  11. Xiong, Tao & Li, Chongguang & Bao, Yukun, 2017. "Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model," Economic Modelling, Elsevier, vol. 60(C), pages 11-23.
  12. Yan Sun & Guanghua Lian & Zudi Lu & Jennifer Loveland & Isaac Blackhurst, 2020. "Modeling the Variance of Return Intervals Toward Volatility Prediction," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 492-519, July.
  13. Hao, Peng & Guo, Junpeng, 2017. "Constrained center and range joint model for interval-valued symbolic data regression," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 106-138.
  14. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
  15. Dias, Sónia & Brito, Paula, 2017. "Off the beaten track: A new linear model for interval data," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1118-1130.
  16. Sun, Shaolong & Sun, Yuying & Wang, Shouyang & Wei, Yunjie, 2018. "Interval decomposition ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 76(C), pages 274-287.
  17. Marta García-Bárzana & Ana Belén Ramos-Guajardo & Ana Colubi & Erricos J. Kontoghiorghes, 2020. "Multiple linear regression models for random intervals: a set arithmetic approach," Computational Statistics, Springer, vol. 35(2), pages 755-773, June.
  18. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
  19. Blanco-Fernández, Angela & Corral, Norberto & González-Rodríguez, Gil, 2011. "Estimation of a flexible simple linear model for interval data based on set arithmetic," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2568-2578, September.
  20. Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2018. "Prediction Regions for Interval-valued Time Series," Working Papers 201817, University of California at Riverside, Department of Economics.
  21. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
  22. Gloria Gonzalez-Rivera & Wei Lin, 2014. "Interval-valued Time Series: Model Estimation based on Order Statistics," Working Papers 201429, University of California at Riverside, Department of Economics.
  23. Carlo Drago & Roberto Ricciuti, 2019. "An interval variables approach to address measurement uncertainty in governance indicators," Economics Bulletin, AccessEcon, vol. 39(1), pages 626-635.
  24. Gloria Gonzalez-Rivera & Javier Arroyo & Carlos Mate, 2011. "Forecasting with Interval and Histogram Data. Some Financial Applications," Working Papers 201438, University of California at Riverside, Department of Economics.
  25. Hui Qu & Mengying He, 2022. "Predicting Volatility Based on Interval Regression Models," JRFM, MDPI, vol. 15(12), pages 1-21, November.
  26. Karel Hron & Paula Brito & Peter Filzmoser, 2017. "Exploratory data analysis for interval compositional data," 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(2), pages 223-241, June.
  27. A. Pedro Duarte Silva & Peter Filzmoser & Paula Brito, 2018. "Outlier detection in interval data," 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. 12(3), pages 785-822, September.
  28. Paulo M.M. Rodrigues & Nazarii Salish, 2011. "Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns," Working Papers w201128, Banco de Portugal, Economics and Research Department.
  29. Sun, Yuying & Zhang, Xun & Hong, Yongmiao & Wang, Shouyang, 2019. "Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling," Energy Economics, Elsevier, vol. 78(C), pages 165-173.
  30. Cheolwoo Park & Yongho Jeon & Kee-Hoon Kang, 2016. "An exploratory data analysis in scale-space for interval-valued data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2643-2660, October.
  31. Gloria Gonzalez-Rivera & Yun Luo, 2020. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202005, University of California at Riverside, Department of Economics.
  32. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt's exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759, July.
  33. Leandro Maciel & Rosangela Ballini, 2021. "Functional Fuzzy Rule-Based Modeling for Interval-Valued Data: An Empirical Application for Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 743-771, February.
  34. Chang, Meng-Shiuh & Ju, Peijie & Liu, Yilei & Hsueh, Shao-Chieh, 2022. "Determining hedges and safe havens for stocks using interval analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
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