IDEAS home Printed from https://ideas.repec.org/f/psu601.html
   My authors  Follow this author

Zoey D Su

Personal Details

First Name:Zoey
Middle Name:D
Last Name:Su
Suffix:
RePEc Short-ID:psu601
[This author has chosen not to make the email address public]

Research output

as
Jump to: Working papers Articles

Working papers

  1. Su, Z., 1998. "Successful Managers in International Joint-Ventures in China," Papers 98-024, Laval - Faculte des sciences de administration.
  2. Michel, L. & Su, Z., 1998. "Analyse critique du discours et de la doctrine de la mondialisation," Papers 98-025, Laval - Faculte des sciences de administration.
  3. Poisson, R & Su, Z, 1996. "Les strategies d'internationalisation des P.M.E. Etat actuel des recherches et perspectives," Papers 96-64, Laval - Faculte des sciences de administration.
  4. Chrysostome, E-V & Poulin D & Su, Z & Martel, A, 1996. "Les reseaux de relations de collaboration inter-entreprise : une analyse historique," Papers 96-61, Laval - Faculte des sciences de administration.
  5. Su, Z. & Richelieu, A., 1996. "Western Managers Working in an Environment of "Organized Disorganization": Perception and Attitude Regarding Business Ethics," Papers 96-39, Laval - Faculte des sciences de administration.

Articles

  1. Burger, M. & Su, Z. & De Schutter, B., 2018. "A node current-based 2-index formulation for the fixed-destination multi-depot travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 265(2), pages 463-477.
  2. Z. Su & G. Zhu & X. Chen & Y. Yang, 2016. "Sparse envelope model: efficient estimation and response variable selection in multivariate linear regression," Biometrika, Biometrika Trust, vol. 103(3), pages 579-593.
  3. Yuan, M. & Zhang, L. & Gou, F. & Su, Z. & Spiertz, J.H.J. & van der Werf, W., 2013. "Assessment of crop growth and water productivity for five C3 species in semi-arid Inner Mongolia," Agricultural Water Management, Elsevier, vol. 122(C), pages 28-38.
  4. R. D. Cook & I. S. Helland & Z. Su, 2013. "Envelopes and partial least squares regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(5), pages 851-877, November.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Burger, M. & Su, Z. & De Schutter, B., 2018. "A node current-based 2-index formulation for the fixed-destination multi-depot travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 265(2), pages 463-477.

    Cited by:

    1. Balma, Ali & Salem, Safa Ben & Mrad, Mehdi & Ladhari, Talel, 2018. "Strong multi-commodity flow formulations for the asymmetric traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 271(1), pages 72-79.

  2. Z. Su & G. Zhu & X. Chen & Y. Yang, 2016. "Sparse envelope model: efficient estimation and response variable selection in multivariate linear regression," Biometrika, Biometrika Trust, vol. 103(3), pages 579-593.

    Cited by:

    1. D. J. Eck & R. D. Cook, 2017. "Weighted envelope estimation to handle variability in model selection," Biometrika, Biometrika Trust, vol. 104(3), pages 743-749.
    2. Minji Lee & Zhihua Su, 2020. "A Review of Envelope Models," International Statistical Review, International Statistical Institute, vol. 88(3), pages 658-676, December.
    3. Dennis Cook, R. & Forzani, Liliana, 2023. "On the role of partial least squares in path analysis for the social sciences," Journal of Business Research, Elsevier, vol. 167(C).
    4. Hu, Jianhua & Liu, Xiaoqian & Liu, Xu & Xia, Ningning, 2022. "Some aspects of response variable selection and estimation in multivariate linear regression," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    5. S. Yaser Samadi & Wiranthe B. Herath, 2023. "Reduced-rank Envelope Vector Autoregressive Models," Papers 2309.12902, arXiv.org.
    6. Yue Zhao & Ingrid Van Keilegom & Shanshan Ding, 2022. "Envelopes for censored quantile regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1562-1585, December.
    7. Alexander M. Franks, 2022. "Reducing subspace models for large‐scale covariance regression," Biometrics, The International Biometric Society, vol. 78(4), pages 1604-1613, December.
    8. Jain Yashita & Ding Shanshan & Qiu Jing, 2019. "Sliced inverse regression for integrative multi-omics data analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(1), pages 1-13, February.
    9. Guo, Wenxing & Balakrishnan, Narayanaswamy & He, Mu, 2023. "Envelope-based sparse reduced-rank regression for multivariate linear model," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    10. An, Baiguo & Zhang, Beibei, 2017. "Simultaneous selection of predictors and responses for high dimensional multivariate linear regression," Statistics & Probability Letters, Elsevier, vol. 127(C), pages 173-177.
    11. Lan Liu & Wei Li & Zhihua Su & Dennis Cook & Luca Vizioli & Essa Yacoub, 2022. "Efficient estimation via envelope chain in magnetic resonance imaging‐based studies," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 481-501, June.

  3. Yuan, M. & Zhang, L. & Gou, F. & Su, Z. & Spiertz, J.H.J. & van der Werf, W., 2013. "Assessment of crop growth and water productivity for five C3 species in semi-arid Inner Mongolia," Agricultural Water Management, Elsevier, vol. 122(C), pages 28-38.

    Cited by:

    1. Chen, Yongfan & Zhang, Zeshan & Wang, Xuejiao & Sun, Shuai & Zhang, Yutong & Wang, Sen & Yang, Mingfeng & Ji, Fen & Ji, Chunrong & Xiang, Dao & Zha, Tianshan & Zhang, Lizhen, 2022. "Sap velocity, transpiration and water use efficiency of drip-irrigated cotton in response to chemical topping and row spacing," Agricultural Water Management, Elsevier, vol. 267(C).
    2. Zhang, Yue & Duan, Yu & Nie, Jiayi & Yang, Jie & Ren, Jianhong & van der Werf, Wopke & Evers, Jochem B. & Zhang, Jun & Su, Zhicheng & Zhang, Lizhen, 2019. "A lack of complementarity for water acquisition limits yield advantage of oats/vetch intercropping in a semi-arid condition," Agricultural Water Management, Elsevier, vol. 225(C).
    3. Ahmadzadeh Araji, Hamidreza & Wayayok, Aimrun & Massah Bavani, Alireza & Amiri, Ebrahim & Abdullah, Ahmad Fikri & Daneshian, Jahanfar & Teh, C.B.S., 2018. "Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models," Agricultural Water Management, Elsevier, vol. 205(C), pages 63-71.
    4. Li, S.X. & Wang, Z.H. & Li, S.Q. & Gao, Y.J., 2015. "Effect of nitrogen fertilization under plastic mulched and non-plastic mulched conditions on water use by maize plants in dryland areas of China," Agricultural Water Management, Elsevier, vol. 162(C), pages 15-32.
    5. Dhouib, M. & Zitouna-Chebbi, R. & Prévot, L. & Molénat, J. & Mekki, I. & Jacob, F., 2022. "Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem," Agricultural Water Management, Elsevier, vol. 273(C).
    6. Chen, Xin & Jiang, Li & Zhang, Guoliang & Meng, Lijun & Pan, Zhihua & Lun, Fei & An, Pingli, 2021. "Green-depressing cropping system: A referential land use practice for fallow to ensure a harmonious human-land relationship in the farming-pastoral ecotone of northern China," Land Use Policy, Elsevier, vol. 100(C).
    7. Nyathi, M.K. & van Halsema, G.E. & Annandale, J.G. & Struik, P.C., 2018. "Calibration and validation of the AquaCrop model for repeatedly harvested leafy vegetables grown under different irrigation regimes," Agricultural Water Management, Elsevier, vol. 208(C), pages 107-119.

  4. R. D. Cook & I. S. Helland & Z. Su, 2013. "Envelopes and partial least squares regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(5), pages 851-877, November.

    Cited by:

    1. May, Paul & Biesecker, Matthew & Rekabdarkolaee, Hossein Moradi, 2022. "Response envelopes for linear coregionalization models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    2. Zhang, Xin & Wang, Chong & Wu, Yichao, 2018. "Functional envelope for model-free sufficient dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 163(C), pages 37-50.
    3. Lasanthi C. R. Pelawa Watagoda & David J. Olive, 2021. "Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals," Statistical Papers, Springer, vol. 62(5), pages 2407-2431, October.
    4. D. J. Eck & R. D. Cook, 2017. "Weighted envelope estimation to handle variability in model selection," Biometrika, Biometrika Trust, vol. 104(3), pages 743-749.
    5. Minji Lee & Zhihua Su, 2020. "A Review of Envelope Models," International Statistical Review, International Statistical Institute, vol. 88(3), pages 658-676, December.
    6. Li, Gen & Yang, Dan & Nobel, Andrew B. & Shen, Haipeng, 2016. "Supervised singular value decomposition and its asymptotic properties," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 7-17.
    7. Dennis Cook, R. & Forzani, Liliana, 2023. "On the role of partial least squares in path analysis for the social sciences," Journal of Business Research, Elsevier, vol. 167(C).
    8. Cook, R. Dennis & Forzani, Liliana & Su, Zhihua, 2016. "A note on fast envelope estimation," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 42-54.
    9. Yue Zhao & Ingrid Van Keilegom & Shanshan Ding, 2022. "Envelopes for censored quantile regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1562-1585, December.
    10. Li, Ying & Udén, Peter & von Rosen, Dietrich, 2015. "A two-step estimation method for grouped data with connections to the extended growth curve model and partial least squares regression," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 347-359.
    11. Cook, R. Dennis, 2022. "A slice of multivariate dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    12. Iaci, Ross & Yin, Xiangrong & Zhu, Lixing, 2016. "The Dual Central Subspaces in dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 178-189.
    13. Alexander M. Franks, 2022. "Reducing subspace models for large‐scale covariance regression," Biometrics, The International Biometric Society, vol. 78(4), pages 1604-1613, December.
    14. Bousebata, Meryem & Enjolras, Geoffroy & Girard, Stéphane, 2023. "Extreme partial least-squares," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    15. Jung, Sungkyu, 2018. "Continuum directions for supervised dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 27-43.
    16. Ekvall, Karl Oskar, 2022. "Targeted principal components regression," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    17. Yeonhee Park & Zhihua Su & Hongtu Zhu, 2017. "Groupwise envelope models for imaging genetic analysis," Biometrics, The International Biometric Society, vol. 73(4), pages 1243-1253, December.
    18. Jain Yashita & Ding Shanshan & Qiu Jing, 2019. "Sliced inverse regression for integrative multi-omics data analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(1), pages 1-13, February.
    19. Cook, R. Dennis & Forzani, Liliana & Liu, Lan, 2023. "Partial least squares for simultaneous reduction of response and predictor vectors in regression," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    20. Qiang Sun & Hongtu Zhu & Yufeng Liu & Joseph G. Ibrahim, 2015. "SPReM: Sparse Projection Regression Model For High-Dimensional Linear Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 289-302, March.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Zoey D Su should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.