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Michail Tsagris

Personal Details

First Name:Michail
Middle Name:
Last Name:Tsagris
Suffix:
RePEc Short-ID:pts186
[This author has chosen not to make the email address public]
https://economics.soc.uoc.gr/en/staff/37351/17

Affiliation

Department of Economics
University of Crete

Rethymnon, Greece
http://www.soc.uoc.gr/
RePEc:edi:deuchgr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Michail Tsagris, 2024. "Constrained Least Squares Simplicial-Simplicial Regression," Working Papers 2402, University of Crete, Department of Economics.
  2. Giorgos Foutzopoulos & Nikolaos Pandis & Michail Tsagris, 2024. "Predicting Full Retirement Attainment of NBA Players," Working Papers 2403, University of Crete, Department of Economics.
  3. Konstantinos Mattas & Michail Tsagris & Vangelis Tzouvelekas, 2024. "Using Synthetic Farm Data to Estimate Individual Nitrate Leaching Levels," Working Papers 2401, University of Crete, Department of Economics.
  4. Michail Tsagris & Abdulaziz Alenazi & Connie Stewart, 2023. "Flexible Non-parametric Regression Models for Compositional Response Data with Zeros," Working Papers 2306, University of Crete, Department of Economics.
  5. Konstantinos Chatzimichael & Charoula Daskalaki & Gregory Emvalomatis & Michail Tsagris & Vangelis Tzouvelekas, 2023. "Factors Shaping Innovative Behavior: A Meta-Analysis of Technology Adoption Studies in Agriculture," Working Papers 2301, University of Crete, Department of Economics.
  6. Aisha Fayomi & Yannis Pantazis & Michail Tsagris & Andrew Wood, 2023. "Cauchy Robust Principal Component Analysis with Applications to High-Dimensional Data Sets," Working Papers 2304, University of Crete, Department of Economics.
  7. Michail Tsagris & Omar Alzeley, 2023. "Circular and Spherical Projected Cauchy Distributions," Working Papers 2305, University of Crete, Department of Economics.
  8. Michail Tsagris & Vangelis Tzouvelekas, 2021. "Nitrate Pollution and Efficiency Measurement in Intensive Farming Systems: A Parametric By-Production Technology Approach," Working Papers 2101, University of Crete, Department of Economics.
  9. Michail Tsagris & Abdulaziz Alenazi, 2019. "Comparison of discriminant analysis methods on the sphere," Working Papers 1902, University of Crete, Department of Economics.
  10. Michail Tsagris & Abdulaziz Alenazi, 2018. "Discriminant Analysis with Spherical Data," Working Papers 1804, University of Crete, Department of Economics.
  11. Michail Tsagris, 2018. "Modelling Structural Zeros in Compositional Data," Working Papers 1803, University of Crete, Department of Economics.
  12. Tsagris, Michail, 2017. "Conditional Independence test for categorical data using Poisson log-linear model," MPRA Paper 79464, University Library of Munich, Germany.
  13. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Nonparametric hypothesis testing for equality of means on the simplex," MPRA Paper 72771, University Library of Munich, Germany.
  14. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.
  15. Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2016. "Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets," MPRA Paper 72772, University Library of Munich, Germany.
  16. Tsagris, Michail, 2015. "Regression analysis with compositional data containing zero values," MPRA Paper 67868, University Library of Munich, Germany.
  17. Tsagris, Michail, 2015. "A novel, divergence based, regression for compositional data," MPRA Paper 72769, University Library of Munich, Germany.
  18. Meriem Rjiba, Meriem & Tsagris, Michail & Mhalla, Hedi, 2015. "Bootstrap for Value at Risk Prediction," MPRA Paper 68842, University Library of Munich, Germany.
  19. Fragkos, Konstantinos C. & Tsagris, Michail & Frangos, Christos C., 2014. "Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number," MPRA Paper 66451, University Library of Munich, Germany.
  20. Tsagris, Michail, 2014. "The k-NN algorithm for compositional data: a revised approach with and without zero values present," MPRA Paper 65866, University Library of Munich, Germany.
  21. Tsagris, Michail & Beneki, Christina & Hassani, Hossein, 2013. "On the Folded Normal Distribution," MPRA Paper 53748, University Library of Munich, Germany.
  22. Tsagris, Michail & Elmatzoglou, Ioannis & C. Frangos, Christos, 2012. "Assessment of Performance of Correlation Estimates in Discrete Bivariate Distributions using Bootstrap Methodology," MPRA Paper 68057, University Library of Munich, Germany.
  23. T. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2011. "A data-based power transformation for compositional data," MPRA Paper 53068, University Library of Munich, Germany.

Articles

  1. Charlotte Fabri & Michail Tsagris & Michele Moretti & Steven Van Passel, 2024. "Adaptation to climate change: The irrigation technology mix of Italian farmers," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(2), pages 781-802, June.
  2. Michail Tsagris & Vangelis Tzouvelekas, 2022. "Nitrate leaching and efficiency measurement in intensive farming systems: A parametric by‐production technology approach," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 633-647, July.
  3. Michail Tsagris, 2022. "The FEDHC Bayesian Network Learning Algorithm," Mathematics, MDPI, vol. 10(15), pages 1-28, July.
  4. Alexandros Gkatsikos & Dimitrios Natos & Christos Staboulis & Konstadinos Mattas & Michail Tsagris & Apostolos Polymeros, 2022. "An Impact Assessment of the Young Farmers Scheme Policy on Regional Growth in Greece," Sustainability, MDPI, vol. 14(5), pages 1-12, March.
  5. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
  6. Yannis Pantazis & Michail Tsagris & Andrew T. A. Wood, 2019. "Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 63-82, February.
  7. Alharbi N & Tsagris M, 2018. "Confidence Intervals for the Relative Risk," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 4(5), pages 113-117, February.
  8. Konstantinos C. Fragkos & Michail Tsagris & Christos C. Frangos, 2017. "Exploring the distribution for the estimator of Rosenthal's ‘fail-safe’ number of unpublished studies in meta-analysis," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(11), pages 5672-5684, June.
  9. Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2017. "Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i07).
  10. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.
  11. J. L. Scealy & Patrice de Caritat & Eric C. Grunsky & Michail T. Tsagris & A. H. Welsh, 2015. "Robust Principal Component Analysis for Power Transformed Compositional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 136-148, March.
  12. Meriem Rjiba & Michail Tsagris & Hedi Mhalla, 2015. "Bootstrap for Value at Risk Prediction," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(6), pages 362-371.
  13. Michail Tsagris & Christina Beneki & Hossein Hassani, 2014. "On the Folded Normal Distribution," Mathematics, MDPI, vol. 2(1), pages 1-17, February.
  14. Michail Tsagris, 2014. "Statistics through resampling methods and R, second edition," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(12), pages 2780-2781, December.

Chapters

  1. Michail Tsagris & Stefanos Fafalios, 2022. "Advanced Car Price Modelling and Prediction," Contributions to Economics, in: M. Kenan Terzioğlu (ed.), Advances in Econometrics, Operational Research, Data Science and Actuarial Studies, pages 479-494, Springer.
  2. Ioanna Papadaki & Michail Tsagris, 2022. "Are NBA Players’ Salaries in Accordance with Their Performance on Court?," Contributions to Economics, in: M. Kenan Terzioğlu (ed.), Advances in Econometrics, Operational Research, Data Science and Actuarial Studies, pages 405-428, Springer.

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

  1. Michail Tsagris & Abdulaziz Alenazi & Connie Stewart, 2023. "Flexible Non-parametric Regression Models for Compositional Response Data with Zeros," Working Papers 2306, University of Crete, Department of Economics.

    Cited by:

    1. Yang, Bowen & Wang, Dafang & Yu, Beike & Wang, Facheng & Chen, Shiqin & Sun, Xu & Dong, Haosong, 2024. "Research on online passive electrochemical impedance spectroscopy and its outlook in battery management," Applied Energy, Elsevier, vol. 363(C).

  2. Michail Tsagris & Vangelis Tzouvelekas, 2021. "Nitrate Pollution and Efficiency Measurement in Intensive Farming Systems: A Parametric By-Production Technology Approach," Working Papers 2101, University of Crete, Department of Economics.

    Cited by:

    1. Chunlin Hua & Jiuhong Zhang & Zhiru Long & Richard T. Woodward, 2023. "Effects of Policy for Controlling Agricultural Non-Point Source Pollution in China: From a Perspective of Regional and Policy Measures Differences," IJERPH, MDPI, vol. 20(4), pages 1-19, February.

  3. Michail Tsagris & Abdulaziz Alenazi, 2019. "Comparison of discriminant analysis methods on the sphere," Working Papers 1902, University of Crete, Department of Economics.

    Cited by:

    1. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    2. Giuseppe Pandolfo & Antonio D’ambrosio, 2023. "Clustering directional data through depth functions," Computational Statistics, Springer, vol. 38(3), pages 1487-1506, September.

  4. Michail Tsagris, 2018. "Modelling Structural Zeros in Compositional Data," Working Papers 1803, University of Crete, Department of Economics.

    Cited by:

    1. Charlotte Fabri & Michail Tsagris & Michele Moretti & Steven Van Passel, 2024. "Adaptation to climate change: The irrigation technology mix of Italian farmers," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(2), pages 781-802, June.

  5. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Nonparametric hypothesis testing for equality of means on the simplex," MPRA Paper 72771, University Library of Munich, Germany.

    Cited by:

    1. Philippos Louis & Orestis Troumpounis & Nikolaos Tsakas & Dimitrios Xefteris, 2020. "Protest voting in the laboratory," Working Papers 288072952, Lancaster University Management School, Economics Department.

  6. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.

    Cited by:

    1. Wang, Dieter & Andrée, Bo Pieter Johannes & Chamorro, Andres Fernando & Spencer, Phoebe Girouard, 2022. "Transitions into and out of food insecurity: A probabilistic approach with panel data evidence from 15 countries," World Development, Elsevier, vol. 159(C).
    2. Yannis Pantazis & Michail Tsagris & Andrew T. A. Wood, 2019. "Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 63-82, February.
    3. Wang,Dieter & Andree,Bo Pieter Johannes & Chamorro Elizondo,Andres Fernando & Spencer,Phoebe Girouard, 2020. "Stochastic Modeling of Food Insecurity," Policy Research Working Paper Series 9413, The World Bank.

  7. Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2016. "Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets," MPRA Paper 72772, University Library of Munich, Germany.

    Cited by:

    1. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
    2. Sašo Karakatič, 2020. "EvoPreprocess—Data Preprocessing Framework with Nature-Inspired Optimization Algorithms," Mathematics, MDPI, vol. 8(6), pages 1-29, June.

  8. Tsagris, Michail, 2015. "Regression analysis with compositional data containing zero values," MPRA Paper 67868, University Library of Munich, Germany.

    Cited by:

    1. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
    2. Matt Kammer-Kerwick & Kara Takasaki & J. Bruce Kellison & Jeff Sternberg, 2022. "Asset-Based, Sustainable Local Economic Development: Using Community Participation to Improve Quality of Life Across Rural, Small-Town, and Urban Communities," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(5), pages 3023-3047, October.

  9. Meriem Rjiba, Meriem & Tsagris, Michail & Mhalla, Hedi, 2015. "Bootstrap for Value at Risk Prediction," MPRA Paper 68842, University Library of Munich, Germany.

    Cited by:

    1. Kakade, Kshitij & Jain, Ishan & Mishra, Aswini Kumar, 2022. "Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach," Resources Policy, Elsevier, vol. 78(C).

  10. Fragkos, Konstantinos C. & Tsagris, Michail & Frangos, Christos C., 2014. "Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number," MPRA Paper 66451, University Library of Munich, Germany.

    Cited by:

    1. Pan, Xu & Wong, Christina W.Y. & Chee Yew Wong, & Boon-itt, Sakun & Li, Chunsheng, 2024. "The influences of circular economy practices on manufacturing firm's performance: A meta-analytic structural equation modeling study," International Journal of Production Economics, Elsevier, vol. 273(C).
    2. Marie-Christine Payette & Claude Bélanger & Vanessa Léveillé & Sébastien Grenier, 2016. "Fall-Related Psychological Concerns and Anxiety among Community-Dwelling Older Adults: Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-17, April.
    3. Hui-Wen Tseng & Fan-Hao Chou & Ching-Hsiu Chen & Yu-Ping Chang, 2023. "Effects of Mindfulness-Based Cognitive Therapy on Major Depressive Disorder with Multiple Episodes: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 20(2), pages 1-16, January.

  11. Tsagris, Michail & Beneki, Christina & Hassani, Hossein, 2013. "On the Folded Normal Distribution," MPRA Paper 53748, University Library of Munich, Germany.

    Cited by:

    1. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    2. Katarzyna Budnik & Gerhard Rünstler, 2023. "Identifying structural VARs from sparse narrative instruments: Dynamic effects of US macroprudential policies," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 186-201, March.
    3. Mardia, Kanti V. & Wiechers, Henrik & Eltzner, Benjamin & Huckemann, Stephan F., 2022. "Principal component analysis and clustering on manifolds," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    4. Shi, Yan & Lu, Zhenzhou & He, Ruyang & Zhou, Yicheng & Chen, Siyu, 2020. "A novel learning function based on Kriging for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    5. Shi, Wen & Zhou, Qing & Zhou, Yanju, 2023. "An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2020. "Risk Analysis through the Half-Normal Distribution," Mathematics, MDPI, vol. 8(11), pages 1-27, November.
    7. Qiwei Xie & Linda L. Zhang & Haichao Shang & Ali Emrouznejad & Yongjun Li, 2021. "Evaluating performance of super-efficiency models in ranking efficient decision-making units based on Monte Carlo simulations," Annals of Operations Research, Springer, vol. 305(1), pages 273-323, October.

  12. Tsagris, Michail & Elmatzoglou, Ioannis & C. Frangos, Christos, 2012. "Assessment of Performance of Correlation Estimates in Discrete Bivariate Distributions using Bootstrap Methodology," MPRA Paper 68057, University Library of Munich, Germany.

    Cited by:

    1. Fragkos, Konstantinos C. & Tsagris, Michail & Frangos, Christos C., 2014. "Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number," MPRA Paper 66451, University Library of Munich, Germany.

  13. T. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2011. "A data-based power transformation for compositional data," MPRA Paper 53068, University Library of Munich, Germany.

    Cited by:

    1. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.
    2. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.
    3. Tsagris, Michail, 2015. "Regression analysis with compositional data containing zero values," MPRA Paper 67868, University Library of Munich, Germany.
    4. Yannis Pantazis & Michail Tsagris & Andrew T. A. Wood, 2019. "Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 63-82, February.
    5. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Nonparametric hypothesis testing for equality of means on the simplex," MPRA Paper 72771, University Library of Munich, Germany.

Articles

  1. Michail Tsagris & Vangelis Tzouvelekas, 2022. "Nitrate leaching and efficiency measurement in intensive farming systems: A parametric by‐production technology approach," Agricultural Economics, International Association of Agricultural Economists, vol. 53(4), pages 633-647, July.

    Cited by:

    1. Haleh Delnava & Kristiaan Kerstens & Timo Kuosmanen & Zhiyang Shen, 2024. "Semi-parametric Estimation of Convex and Nonconvex By-Production Technologies," Working Papers 2024-EQM-02, IESEG School of Management.
    2. Zhu, Ning & Streimikis, Justas & Yu, Zhiqian & Balezentis, Tomas, 2023. "Energy-sustainable agriculture in the European Union member states: Overall productivity growth and structural efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

  2. Michail Tsagris, 2022. "The FEDHC Bayesian Network Learning Algorithm," Mathematics, MDPI, vol. 10(15), pages 1-28, July.

    Cited by:

    1. Snezhana Gocheva-Ilieva & Atanas Ivanov & Hristina Kulina, 2023. "Special Issue “Statistical Data Modeling and Machine Learning with Applications II”," Mathematics, MDPI, vol. 11(12), pages 1-4, June.
    2. Monica Aureliana Petcu & Liliana Ionescu-Feleaga & Bogdan-Ștefan Ionescu & Dumitru-Florin Moise, 2023. "A Decade for the Mathematics : Bibliometric Analysis of Mathematical Modeling in Economics, Ecology, and Environment," Mathematics, MDPI, vol. 11(2), pages 1-30, January.

  3. Alexandros Gkatsikos & Dimitrios Natos & Christos Staboulis & Konstadinos Mattas & Michail Tsagris & Apostolos Polymeros, 2022. "An Impact Assessment of the Young Farmers Scheme Policy on Regional Growth in Greece," Sustainability, MDPI, vol. 14(5), pages 1-12, March.

    Cited by:

    1. Stavros Kalogiannidis & Simeon Karafolas & Fotios Chatzitheodoridis, 2024. "The Key Role of Cooperatives in Sustainable Agriculture and Agrifood Security: Evidence from Greece," Sustainability, MDPI, vol. 16(16), pages 1-20, August.
    2. Áron József Borda & Balázs Sárvári & Jeremiás Máté Balogh, 2023. "Generation Change in Agriculture: A Systematic Review of the Literature," Economies, MDPI, vol. 11(5), pages 1-15, April.
    3. George Malindretos & Eleni Sardianou & Maria Briana, 2023. "Farmers’ Perception on Contract Farming in the Post-COVID Era: Empirical Study in Greece," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    4. Anna Carbone & Felicetta Carillo & Pavel Ciaian & Roberta Sardone & Federico Antonioli & Juan Tur Cardona, 2024. "Does the European Union Start-Up Aid Help Young Farmers to Innovate and to Join Networks?," Agriculture, MDPI, vol. 14(10), pages 1-23, October.
    5. Stavros Kalogiannidis & Christina-Ioanna Papadopoulou & Efstratios Loizou & Fotios Chatzitheodoridis, 2023. "Risk, Vulnerability, and Resilience in Agriculture and Their Impact on Sustainable Rural Economy Development: A Case Study of Greece," Agriculture, MDPI, vol. 13(6), pages 1-20, June.

  4. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.

    Cited by:

    1. Michail Tsagris, 2022. "The FEDHC Bayesian Network Learning Algorithm," Mathematics, MDPI, vol. 10(15), pages 1-28, July.

  5. Alharbi N & Tsagris M, 2018. "Confidence Intervals for the Relative Risk," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 4(5), pages 113-117, February.

    Cited by:

    1. Mai Zhou, 2018. "Confidence Intervals for Relative Risk by Likelihood Ratio Test," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 6(5), pages 151-154, May.

  6. Lagani, Vincenzo & Athineou, Giorgos & Farcomeni, Alessio & Tsagris, Michail & Tsamardinos, Ioannis, 2017. "Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i07).
    See citations under working paper version above.
  7. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.

    Cited by:

    1. Wang, Dieter & Andrée, Bo Pieter Johannes & Chamorro, Andres Fernando & Spencer, Phoebe Girouard, 2022. "Transitions into and out of food insecurity: A probabilistic approach with panel data evidence from 15 countries," World Development, Elsevier, vol. 159(C).
    2. Yannis Pantazis & Michail Tsagris & Andrew T. A. Wood, 2019. "Gaussian Asymptotic Limits for the α-transformation in the Analysis of Compositional Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 63-82, February.
    3. Wang,Dieter & Andree,Bo Pieter Johannes & Chamorro Elizondo,Andres Fernando & Spencer,Phoebe Girouard, 2020. "Stochastic Modeling of Food Insecurity," Policy Research Working Paper Series 9413, The World Bank.

  8. J. L. Scealy & Patrice de Caritat & Eric C. Grunsky & Michail T. Tsagris & A. H. Welsh, 2015. "Robust Principal Component Analysis for Power Transformed Compositional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 136-148, March.

    Cited by:

    1. Marco Stefanucci & Stefano Mazzuco, 2022. "Analysing cause‐specific mortality trends using compositional functional data analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 61-83, January.
    2. Huiwen Wang & Zhichao Wang & Shanshan Wang, 2021. "Sliced inverse regression method for multivariate compositional data modeling," Statistical Papers, Springer, vol. 62(1), pages 361-393, February.
    3. Kokoszka, Piotr & Miao, Hong & Petersen, Alexander & Shang, Han Lin, 2019. "Forecasting of density functions with an application to cross-sectional and intraday returns," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1304-1317.
    4. J. L. Scealy & A. H. Welsh, 2017. "A Directional Mixed Effects Model for Compositional Expenditure Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 24-36, January.
    5. Liang, Wanfeng & Wu, Yue & Ma, Xiaoyan, 2022. "Robust sparse precision matrix estimation for high-dimensional compositional data," Statistics & Probability Letters, Elsevier, vol. 184(C).

  9. Meriem Rjiba & Michail Tsagris & Hedi Mhalla, 2015. "Bootstrap for Value at Risk Prediction," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(6), pages 362-371.
    See citations under working paper version above.
  10. Michail Tsagris & Christina Beneki & Hossein Hassani, 2014. "On the Folded Normal Distribution," Mathematics, MDPI, vol. 2(1), pages 1-17, February.
    See citations under working paper version above.

Chapters

    Sorry, no citations of chapters recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 19 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (14) 2015-08-13 2015-09-11 2015-11-21 2016-02-29 2016-08-07 2016-08-07 2016-08-07 2017-06-04 2018-10-15 2018-10-15 2023-03-13 2023-03-13 2023-03-20 2024-04-15. Author is listed
  2. NEP-CSE: Economics of Strategic Management (4) 2016-08-07 2016-08-07 2016-08-07 2023-03-20
  3. NEP-AGE: Economics of Ageing (2) 2024-05-06 2024-09-16
  4. NEP-AGR: Agricultural Economics (2) 2023-03-20 2024-02-19
  5. NEP-BIG: Big Data (2) 2024-05-06 2024-09-16
  6. NEP-DCM: Discrete Choice Models (2) 2017-06-04 2023-03-20
  7. NEP-SPO: Sports and Economics (2) 2024-05-06 2024-09-16
  8. NEP-CMP: Computational Economics (1) 2016-08-07
  9. NEP-ENV: Environmental Economics (1) 2021-01-18
  10. NEP-ETS: Econometric Time Series (1) 2023-03-13
  11. NEP-ORE: Operations Research (1) 2021-01-18
  12. NEP-RMG: Risk Management (1) 2016-02-29

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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.