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My authors Follow this authorPedro Duarte Silva
Personal Details
First Name: | Pedro |
Middle Name: | Duarte |
Last Name: | Silva |
Suffix: | |
RePEc Short-ID: | psi537 |
[This author has chosen not to make the email address public] | |
Affiliation
Católica Porto Business School
Universidade Católica Portuguesa
Porto, Portugalhttp://www.catolicabs.porto.ucp.pt/
RePEc:edi:feucppt (more details at EDIRC)
Research output
Jump to: Working papers Articles ChaptersWorking papers
- A. Pedro Duarte Silva, 2009. "Exact and heuristic algorithms for variable selection: Extended Leaps and Bounds," Working Papers de Economia (Economics Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
- Pedro Duarte Silva, 2009. "LINEAR DISCRIMINANT RULES for HIGH-DIMENSIONAL CORRELATED DATA: ASYMPTOTIC and FINITE SAMPLE RESULTS," Working Papers de Gestão (Management Working Papers) 09, Católica Porto Business School, Universidade Católica Portuguesa.
- A. Pedro Duarte Silva, 2000. "DISCARDING VARIABLES in PRINCIPAL COMPONENT ANALYSIS : ALGORITHMS for ALL-SUBSETS COMPARISONS," Working Papers de Economia (Economics Working Papers) 02, Católica Porto Business School, Universidade Católica Portuguesa.
- A. Pedro Duarte Silva, 1998. "EFFICIENT SCREENING of VARIABLE SUBSETS in MULTIVARIATE STATISCAL MODELS," Working Papers de Economia (Economics Working Papers) 04, Católica Porto Business School, Universidade Católica Portuguesa.
- A. Pedro Duarte Silva & Antonie Stam & John Neter, 1997. "Two-Group Classification in Business: an Evaluation of Paramatric and Non-Parametric Approaches," Working Papers de Economia (Economics Working Papers) 03, Católica Porto Business School, Universidade Católica Portuguesa.
Articles
- 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.
- Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
- A. Silva & Paula Brito, 2015. "Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
- Paula Brito & A. Pedro Duarte Silva, 2012. "Modelling interval data with Normal and Skew-Normal distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 3-20, March.
- Pedro Duarte Silva, A., 2011. "Two-group classification with high-dimensional correlated data: A factor model approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2975-2990, November.
- António Silva & Paula Brito, 2006. "Linear discriminant analysis for interval data," Computational Statistics, Springer, vol. 21(2), pages 289-308, June.
- Stam, Antonie & Duarte Silva, A. Pedro, 2003. "On multiplicative priority rating methods for the AHP," European Journal of Operational Research, Elsevier, vol. 145(1), pages 92-108, February.
- Duarte Silva, António Pedro, 2001. "Efficient Variable Screening for Multivariate Analysis," Journal of Multivariate Analysis, Elsevier, vol. 76(1), pages 35-62, January.
- Silva, Antonio Pedro Duarte & Stam, Antonie, 1994. "Second order mathematical programming formulations for discriminant analysis," European Journal of Operational Research, Elsevier, vol. 72(1), pages 4-22, January.
Chapters
- Antonie Stam & A. Pedro Duarte Silva, 2000. "Multiplicative Ratings For The Ahp," World Scientific Book Chapters, in: Yong Shi & Milan Zeleny (ed.), New Frontiers Of Decision Making For The Information Technology Era, chapter 18, pages 331-345, World Scientific Publishing Co. Pte. Ltd..
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
- A. Pedro Duarte Silva, 2000.
"DISCARDING VARIABLES in PRINCIPAL COMPONENT ANALYSIS : ALGORITHMS for ALL-SUBSETS COMPARISONS,"
Working Papers de Economia (Economics Working Papers)
02, Católica Porto Business School, Universidade Católica Portuguesa.
Cited by:
- Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
- Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
- Ester Gutiérrez & Sebastián Lozano, 2014. "A DEA Approach to Performance-Based Budgeting of Formula One Constructors," Journal of Sports Economics, , vol. 15(2), pages 180-200, April.
Articles
- 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.
Cited by:
- M. Rosário Oliveira & Margarida Azeitona & António Pacheco & Rui Valadas, 2022. "Association measures for interval variables," 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. 16(3), pages 491-520, September.
- Amin Asadollahi & Binod Ale Magar & Bishal Poudel & Asyeh Sohrabifar & Ajay Kalra, 2024. "Application of Machine Learning Models for Improving Discharge Prediction in Ungauged Watershed: A Case Study in East DuPage, Illinois," Geographies, MDPI, vol. 4(2), pages 1-15, June.
- Pedro Duarte Silva, A., 2017.
"Optimization approaches to Supervised Classification,"
European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
Cited by:
- Blanquero, Rafael & Carrizosa, Emilio & Molero-Río, Cristina & Romero Morales, Dolores, 2020. "Sparsity in optimal randomized classification trees," European Journal of Operational Research, Elsevier, vol. 284(1), pages 255-272.
- Laura Palagi, 2019. "Global optimization issues in deep network regression: an overview," Journal of Global Optimization, Springer, vol. 73(2), pages 239-277, February.
- Emilio Carrizosa & Cristina Molero-Río & Dolores Romero Morales, 2021. "Mathematical optimization in classification and regression trees," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 5-33, April.
- Astorino, Annabella & Avolio, Matteo & Fuduli, Antonio, 2022. "A maximum-margin multisphere approach for binary Multiple Instance Learning," European Journal of Operational Research, Elsevier, vol. 299(2), pages 642-652.
- Baldomero-Naranjo, Marta & Martínez-Merino, Luisa I. & Rodríguez-Chía, Antonio M., 2020. "Tightening big Ms in integer programming formulations for support vector machines with ramp loss," European Journal of Operational Research, Elsevier, vol. 286(1), pages 84-100.
- Baumann, P. & Hochbaum, D.S. & Yang, Y.T., 2019. "A comparative study of the leading machine learning techniques and two new optimization algorithms," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1041-1057.
- Sandra Benítez-Peña & Rafael Blanquero & Emilio Carrizosa & Pepa Ramírez-Cobo, 2019. "On support vector machines under a multiple-cost scenario," 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. 13(3), pages 663-682, September.
- A. Silva & Paula Brito, 2015.
"Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches,"
Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
Cited by:
- Dias, Sónia & Brito, Paula & Amaral, Paula, 2021. "Discriminant analysis of distributional data via fractional programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 206-218.
- M. Rosário Oliveira & Margarida Azeitona & António Pacheco & Rui Valadas, 2022. "Association measures for interval variables," 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. 16(3), pages 491-520, September.
- 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.
- Boris Beranger & Huan Lin & Scott Sisson, 2023. "New models for symbolic data analysis," 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. 17(3), pages 659-699, September.
- Rong Guan & Huiwen Wang & Haitao Zheng, 2020. "Improving accuracy of financial distress prediction by considering volatility: an interval-data-based discriminant model," Computational Statistics, Springer, vol. 35(2), pages 491-514, June.
- Pierpaolo D’Urso & Riccardo Massari & Livia De Giovanni & Carmela Cappelli, 2017. "Exponential distance-based fuzzy clustering for interval-valued data," Fuzzy Optimization and Decision Making, Springer, vol. 16(1), pages 51-70, March.
- Paula Brito & A. Pedro Duarte Silva, 2012.
"Modelling interval data with Normal and Skew-Normal distributions,"
Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 3-20, March.
Cited by:
- 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.
- Sinova, Beatriz & Van Aelst, Stefan, 2015. "On the consistency of a spatial-type interval-valued median for random intervals," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 130-136.
- 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.
- Drago, Carlo, 2016.
"Exploring the Community Structure of Complex Networks,"
ETA: Economic Theory and Applications
244529, Fondazione Eni Enrico Mattei (FEEM).
- Drago, Carlo, 2015. "Exploring the Community Structure of Complex Networks," MPRA Paper 81024, University Library of Munich, Germany.
- Carlo Drago, 2016. "Exploring the Community Structure of Complex Networks," Working Papers 2016.57, Fondazione Eni Enrico Mattei.
- M. Rosário Oliveira & Margarida Azeitona & António Pacheco & Rui Valadas, 2022. "Association measures for interval variables," 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. 16(3), pages 491-520, September.
- Qing Zhao & Huiwen Wang & Shanshan Wang, 2023. "Robust regression for interval-valued data based on midpoints and log-ranges," 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. 17(3), pages 583-621, September.
- 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.
- 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.
- Boris Beranger & Huan Lin & Scott Sisson, 2023. "New models for symbolic data analysis," 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. 17(3), pages 659-699, September.
- A. Silva & Paula Brito, 2015. "Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
- 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.
- Samadi, S. Yaser & Billard, Lynne, 2021. "Analysis of dependent data aggregated into intervals," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
- Liang-Ching Lin & Hsiang-Lin Chien & Sangyeol Lee, 2021. "Symbolic interval-valued data analysis for time series based on auto-interval-regressive models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 295-315, March.
- Pedro Duarte Silva, A., 2011.
"Two-group classification with high-dimensional correlated data: A factor model approach,"
Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2975-2990, November.
Cited by:
- Olivier Ledoit & Michael Wolf, 2013.
"Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions,"
ECON - Working Papers
105, Department of Economics - University of Zurich, revised Jul 2013.
- Ledoit, Olivier & Wolf, Michael, 2015. "Spectrum estimation: A unified framework for covariance matrix estimation and PCA in large dimensions," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 360-384.
- Olivier Ledoit & Michael Wolf, 2013.
"Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions,"
ECON - Working Papers
105, Department of Economics - University of Zurich, revised Jul 2013.
- António Silva & Paula Brito, 2006.
"Linear discriminant analysis for interval data,"
Computational Statistics, Springer, vol. 21(2), pages 289-308, June.
Cited by:
- Angela Blanco-Fernández & Peter Winker, 2016. "Data generation processes and statistical management of interval data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 475-494, October.
- Dias, Sónia & Brito, Paula & Amaral, Paula, 2021. "Discriminant analysis of distributional data via fractional programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 206-218.
- Rong Guan & Huiwen Wang & Haitao Zheng, 2020. "Improving accuracy of financial distress prediction by considering volatility: an interval-data-based discriminant model," Computational Statistics, Springer, vol. 35(2), pages 491-514, June.
- A. Silva & Paula Brito, 2015. "Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
- Stam, Antonie & Duarte Silva, A. Pedro, 2003.
"On multiplicative priority rating methods for the AHP,"
European Journal of Operational Research, Elsevier, vol. 145(1), pages 92-108, February.
Cited by:
- Rajesh Kr. Singh & Angappa Gunasekaran & Pravin Kumar, 2018. "Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach," Annals of Operations Research, Springer, vol. 267(1), pages 531-553, August.
- Gomez-Limon, J.A. & Atance, I., 2004. "Identification of public objectives related to agricultural sector support," Journal of Policy Modeling, Elsevier, vol. 26(8-9), pages 1045-1071, December.
- P Leskinen & J Kangas, 2005. "Rank reversals in multi-criteria decision analysis with statistical modelling of ratio-scale pairwise comparisons," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 855-861, July.
- Francisco J. André & Laura Riesgo, 2006. "A Duality Procedure to Elicit Nonlinear Multiattribute Utility Functions," Working Papers 06.02, Universidad Pablo de Olavide, Department of Economics.
- Alessio Ishizaka & Dieter Balkenborg & Todd Kaplan, 2005.
"Influence of aggregation and measurement scale on ranking a compromise alternative in AHP,"
Discussion Papers
0506, University of Exeter, Department of Economics.
- A Ishizaka & D Balkenborg & T Kaplan, 2011. "Influence of aggregation and measurement scale on ranking a compromise alternative in AHP," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 700-710, April.
- Ishizaka, Alessio & Balkenborg, Dieter & Kaplan, Todd, 2009. "Influence of aggregation and measurement scale on ranking a compromise alternative in AHP," MPRA Paper 19563, University Library of Munich, Germany.
- José A. Gómez-Limón & Ignacio Atance, 2004. "Identification of Public Objectives Related to Agricultural Sector Support," Economic Working Papers at Centro de Estudios Andaluces E2004/57, Centro de Estudios Andaluces.
- Andre, Francisco J. & Riesgo, Laura, 2007. "A non-interactive elicitation method for non-linear multiattribute utility functions: Theory and application to agricultural economics," European Journal of Operational Research, Elsevier, vol. 181(2), pages 793-807, September.
- Ardalan Bafahm & Minghe Sun, 2019. "Some Conflicting Results in the Analytic Hierarchy Process," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 465-486, March.
- Liu, Xianliang & Ma, Yonghao, 2021. "A method to analyze the rank reversal problem in the ELECTRE II method," Omega, Elsevier, vol. 102(C).
- Jordi Gallego-Ayala & Dinis Juízo, 2014. "Integrating Stakeholders’ Preferences into Water Resources Management Planning in the Incomati River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 527-540, January.
- Rodríguez Sousa, A.A. & Parra-López, C. & Sayadi-Gmada, S. & Barandica, J.M. & Rescia, A.J., 2020. "A multifunctional assessment of integrated and ecological farming in olive agroecosystems in southwestern Spain using the Analytic Hierarchy Process," Ecological Economics, Elsevier, vol. 173(C).
- Hahn, Eugene D., 2006. "Link function selection in stochastic multicriteria decision making models," European Journal of Operational Research, Elsevier, vol. 172(1), pages 86-100, July.
- Pranith K. Roy & Krishnendu Shaw, 2023. "A credit scoring model for SMEs using AHP and TOPSIS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 372-391, January.
- Duarte Silva, António Pedro, 2001.
"Efficient Variable Screening for Multivariate Analysis,"
Journal of Multivariate Analysis, Elsevier, vol. 76(1), pages 35-62, January.
Cited by:
- Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
- du Jardin, Philippe & Séverin, Eric, 2012.
"Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time,"
European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.
- du Jardin, Philippe & Severin, Eric, 2011. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," MPRA Paper 39935, University Library of Munich, Germany, revised 03 Apr 2012.
- Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
- Pedro Duarte Silva, A., 2011. "Two-group classification with high-dimensional correlated data: A factor model approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2975-2990, November.
- António Pedro Duarte Silva, 2002. "Discarding Variables in a Principal Component Analysis: Algorithms for All-Subsets Comparisons," Computational Statistics, Springer, vol. 17(2), pages 251-271, July.
- Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
- Ester Gutiérrez & Sebastián Lozano, 2014. "A DEA Approach to Performance-Based Budgeting of Formula One Constructors," Journal of Sports Economics, , vol. 15(2), pages 180-200, April.
- Cadima, Jorge & Cerdeira, J. Orestes & Minhoto, Manuel, 2004. "Computational aspects of algorithms for variable selection in the context of principal components," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 225-236, September.
- Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
- Nkiet, Guy Martial, 2012. "Direct variable selection for discrimination among several groups," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 151-163.
- A. Pedro Duarte Silva, 2009. "Exact and heuristic algorithms for variable selection: Extended Leaps and Bounds," Working Papers de Economia (Economics Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
- Silva, Antonio Pedro Duarte & Stam, Antonie, 1994.
"Second order mathematical programming formulations for discriminant analysis,"
European Journal of Operational Research, Elsevier, vol. 72(1), pages 4-22, January.
Cited by:
- Sueyoshi, Toshiyuki, 2001. "Extended DEA-Discriminant Analysis," European Journal of Operational Research, Elsevier, vol. 131(2), pages 324-351, June.
- Mingue Sun, 2009. "Liquidity Risk and Financial Competition: A Mixed Integer Programming Model for Multiple-Class Discriminant Analysis," Working Papers 0102, College of Business, University of Texas at San Antonio.
- J J Glen, 2005. "Mathematical programming models for piecewise-linear discriminant analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(3), pages 331-341, March.
- Wilson, J. M., 1996. "Integer programming formulations of statistical classification problems," Omega, Elsevier, vol. 24(6), pages 681-688, December.
- A. Pedro Duarte Silva & Antonie Stam & John Neter, 1997. "Two-Group Classification in Business: an Evaluation of Paramatric and Non-Parametric Approaches," Working Papers de Economia (Economics Working Papers) 03, Católica Porto Business School, Universidade Católica Portuguesa.
- Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
- Sueyoshi, Toshiyuki, 2004. "Mixed integer programming approach of extended DEA-discriminant analysis," European Journal of Operational Research, Elsevier, vol. 152(1), pages 45-55, January.
- Sueyoshi, Toshiyuki & Goto, Mika, 2009. "DEA-DA for bankruptcy-based performance assessment: Misclassification analysis of Japanese construction industry," European Journal of Operational Research, Elsevier, vol. 199(2), pages 576-594, December.
- Lam, Kim Fung & Moy, Jane W., 2002. "Combining discriminant methods in solving classification problems in two-group discriminant analysis," European Journal of Operational Research, Elsevier, vol. 138(2), pages 294-301, April.
- Sueyoshi, Toshiyuki, 2006. "DEA-Discriminant Analysis: Methodological comparison among eight discriminant analysis approaches," European Journal of Operational Research, Elsevier, vol. 169(1), pages 247-272, February.
- Stam, Antonie & Ungar, David R., 1995. "RAGNU: A microcomputer package for two-group mathematical programming-based nonparametric classification," European Journal of Operational Research, Elsevier, vol. 86(2), pages 374-388, October.
- J J Glen, 2008. "An additive utility mixed integer programming model for nonlinear discriminant analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1492-1505, November.
- Wanarat, Pradit & Pavur, Robert, 1996. "Examining the effect of second-order terms in mathematical programming approaches to the classification problem," European Journal of Operational Research, Elsevier, vol. 93(3), pages 582-601, September.
- Glen, J.J., 2006. "A comparison of standard and two-stage mathematical programming discriminant analysis methods," European Journal of Operational Research, Elsevier, vol. 171(2), pages 496-515, June.
- Zopounidis, Constantin & Doumpos, Michael, 2002. "Multicriteria classification and sorting methods: A literature review," European Journal of Operational Research, Elsevier, vol. 138(2), pages 229-246, April.
- Ostermark, Ralf & Hoglund, Rune, 1998. "Addressing the multigroup discriminant problem using multivariate statistics and mathematical programming," European Journal of Operational Research, Elsevier, vol. 108(1), pages 224-237, July.
- Sueyoshi, Toshiyuki, 1999. "DEA-discriminant analysis in the view of goal programming," European Journal of Operational Research, Elsevier, vol. 115(3), pages 564-582, June.
Chapters
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More information
Research fields, statistics, top rankings, if available.Statistics
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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 2 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.- NEP-CMP: Computational Economics (1) 2009-01-17
- NEP-ECM: Econometrics (1) 2009-05-16
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