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Ridge Estimators in Logistic Regression

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Cited by:

  1. Esther Calderon-Monge & Ivan Pastor-Sanz & Pilar Huerta-Zavala, 2017. "Economic Sustainability in Franchising: A Model to Predict Franchisor Success or Failure," Sustainability, MDPI, vol. 9(8), pages 1-16, August.
  2. Ejike R. Ugba & Daniel Mörlein & Jan Gertheiss, 2021. "Smoothing in Ordinal Regression: An Application to Sensory Data," Stats, MDPI, vol. 4(3), pages 1-18, July.
  3. Ayanendranath Basu & Abhik Ghosh & Maria Jaenada & Leandro Pardo, 2024. "Robust adaptive LASSO in high-dimensional logistic regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(5), pages 1217-1249, November.
  4. Bolivar-Cime, A. & Marron, J.S., 2013. "Comparison of binary discrimination methods for high dimension low sample size data," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 108-121.
  5. Oh, YeongGwang & Ransikarbum, Kasin & Busogi, Moise & Kwon, Daeil & Kim, Namhun, 2019. "Adaptive SVM-based real-time quality assessment for primer-sealer dispensing process of sunroof assembly line," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 202-212.
  6. André Altmann & Michal Rosen-Zvi & Mattia Prosperi & Ehud Aharoni & Hani Neuvirth & Eugen Schülter & Joachim Büch & Daniel Struck & Yardena Peres & Francesca Incardona & Anders Sönnerborg & Rolf Kaise, 2008. "Comparison of Classifier Fusion Methods for Predicting Response to Anti HIV-1 Therapy," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-9, October.
  7. Chen Lin & Elizabeth W Karlson & Helena Canhao & Timothy A Miller & Dmitriy Dligach & Pei Jun Chen & Raul Natanael Guzman Perez & Yuanyan Shen & Michael E Weinblatt & Nancy A Shadick & Robert M Plenge, 2013. "Automatic Prediction of Rheumatoid Arthritis Disease Activity from the Electronic Medical Records," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-10, August.
  8. Özkale, M. Revan & Arıcan, Engin, 2015. "First-order r−d class estimator in binary logistic regression model," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 19-29.
  9. Angelika Geroldinger & Milan Hronsky & Florian Endel & Gottfried Endel & Rainer Oberbauer & Georg Heinze, 2021. "Estimation of the prevalence of chronic kidney disease in people with diabetes by combining information from multiple routine data collections," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1260-1282, October.
  10. Godichon-Baggioni, Antoine & Lu, Wei & Portier, Bruno, 2024. "Recursive ridge regression using second-order stochastic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
  11. repec:lan:wpaper:4384 is not listed on IDEAS
  12. Luca Insolia & Ana Kenney & Martina Calovi & Francesca Chiaromonte, 2021. "Robust Variable Selection with Optimality Guarantees for High-Dimensional Logistic Regression," Stats, MDPI, vol. 4(3), pages 1-17, August.
  13. Aris Perperoglou, 2011. "Fitting survival data with penalized Poisson regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 451-462, November.
  14. Yu, Tian & Yu, Guang & Wang, Ming-Yang, 2014. "Classification method for detecting coercive self-citation in journals," Journal of Informetrics, Elsevier, vol. 8(1), pages 123-135.
  15. Muhammad Amin & Muhammad Qasim & Muhammad Amanullah & Saima Afzal, 2020. "Performance of some ridge estimators for the gamma regression model," Statistical Papers, Springer, vol. 61(3), pages 997-1026, June.
  16. Aziza Usmanova & Ahmed Aziz & Dilshodjon Rakhmonov & Walid Osamy, 2022. "Utilities of Artificial Intelligence in Poverty Prediction: A Review," Sustainability, MDPI, vol. 14(21), pages 1-39, October.
  17. M. Revan Özkale & Atif Abbasi, 2022. "Iterative restricted OK estimator in generalized linear models and the selection of tuning parameters via MSE and genetic algorithm," Statistical Papers, Springer, vol. 63(6), pages 1979-2040, December.
  18. Paolo Cimbali & Marco De Leonardis & Alessio Fiume & Barbara La Ganga & Luciana Meoli & Marco Orlandi, 2023. "A decision-making rule to detect insufficient data quality - an application of statistical learning techniques to the non-performing loans banking data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Post-pandemic landscape for central bank statistics, volume 58, Bank for International Settlements.
  19. František Dařena & Jan Přichystal, 2018. "Analysis of the Association between Topics in Online Documents and Stock Price Movements," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 66(6), pages 1431-1439.
  20. David Gil & Jose Luis Fernández-Alemán & Juan Trujillo & Ginés García-Mateos & Sergio Luján-Mora & Ambrosio Toval, 2018. "The Effect of Green Software: A Study of Impact Factors on the Correctness of Software," Sustainability, MDPI, vol. 10(10), pages 1-19, September.
  21. Sergio Perez Melo & Zoran Bursac & B.M. Golam Kibria, 2025. "Comparison of Test Statistics for Testing the Regression Coefficients in the Ridge, Liu and Kibria-Lukman Logistic Regression Models: Simulation and Application," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 13(3), pages 1-48, January.
  22. Franz Ratzinger & Harald Bruckschwaiger & Martin Wischenbart & Bernhard Parschalk & Delmiro Fernandez-Reyes & Heimo Lagler & Alexandra Indra & Wolfgang Graninger & Stefan Winkler & Sanjeev Krishna & M, 2012. "Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-6, November.
  23. Peng, Yi & Kou, Gang & Wang, Guoxun & Shi, Yong, 2011. "FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms," Omega, Elsevier, vol. 39(6), pages 677-689, December.
  24. repec:lan:wpaper:4385 is not listed on IDEAS
  25. Mkhadri, A. & Celeux, G. & Nasroallah, A., 1997. "Regularization in discriminant analysis: an overview," Computational Statistics & Data Analysis, Elsevier, vol. 23(3), pages 403-423, January.
  26. Heungsun Hwang & Hye Suk & Yoshio Takane & Jang-Han Lee & Jooseop Lim, 2015. "Generalized Functional Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 101-125, March.
  27. Faisal Zahid & Gerhard Tutz, 2013. "Ridge estimation for multinomial logit models with symmetric side constraints," Computational Statistics, Springer, vol. 28(3), pages 1017-1034, June.
  28. A. Saleh & B. Kibria, 2013. "Improved ridge regression estimators for the logistic regression model," Computational Statistics, Springer, vol. 28(6), pages 2519-2558, December.
  29. Jaroslav Bendl & Jan Stourac & Ondrej Salanda & Antonin Pavelka & Eric D Wieben & Jaroslav Zendulka & Jan Brezovsky & Jiri Damborsky, 2014. "PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-11, January.
  30. Paolo Roma & Merylin Monaro & Laura Muzi & Marco Colasanti & Eleonora Ricci & Silvia Biondi & Christian Napoli & Stefano Ferracuti & Cristina Mazza, 2020. "How to Improve Compliance with Protective Health Measures during the COVID-19 Outbreak: Testing a Moderated Mediation Model and Machine Learning Algorithms," IJERPH, MDPI, vol. 17(19), pages 1-17, October.
  31. Janns Alvaro Patiño-Saucedo & Paola Patricia Ariza-Colpas & Shariq Butt-Aziz & Marlon Alberto Piñeres-Melo & José Luis López-Ruiz & Roberto Cesar Morales-Ortega & Emiro De-la-hoz-Franco, 2022. "Predictive Model for Human Activity Recognition Based on Machine Learning and Feature Selection Techniques," IJERPH, MDPI, vol. 19(19), pages 1-21, September.
  32. Aykut Ekinci & Safa Sen, 2024. "Forecasting Bank Failure in the U.S.: A Cost-Sensitive Approach," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3161-3179, December.
  33. Arvanitakis, K. & Avlonitis, M. & Papadimitriou, E., 2018. "Introducing stochastic recurrence interval to classification algorithms for identifying asperity patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 566-577.
  34. Lambert-Lacroix, Sophie & Peyre, Julie, 2006. "Local likelihood regression in generalized linear single-index models with applications to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2091-2113, December.
  35. Alexander K Seewald & James Cypser & Alexander Mendenhall & Thomas Johnson, 2010. "Quantifying Phenotypic Variation in Isogenic Caenorhabditis elegans Expressing Phsp-16.2::gfp by Clustering 2D Expression Patterns," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-9, July.
  36. M. Aguilera-Morillo & Ana Aguilera & Manuel Escabias & Mariano Valderrama, 2013. "Penalized spline approaches for functional logit regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 251-277, June.
  37. Butaru, Florentin & Chen, Qingqing & Clark, Brian & Das, Sanmay & Lo, Andrew W. & Siddique, Akhtar, 2016. "Risk and risk management in the credit card industry," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 218-239.
  38. Matthew Herland & Richard A. Bauder & Taghi M. Khoshgoftaar, 2020. "Approaches for identifying U.S. medicare fraud in provider claims data," Health Care Management Science, Springer, vol. 23(1), pages 2-19, March.
  39. Ward, Jeremy K. & Cafiero, Florian & Fretigny, Raphael & Colgrove, James & Seror, Valérie, 2019. "France's citizen consultation on vaccination and the challenges of participatory democracy in health," Social Science & Medicine, Elsevier, vol. 220(C), pages 73-80.
  40. Marco-Antonio Moreno-Ibarra & Yenny Villuendas-Rey & Miltiadis D. Lytras & Cornelio Yáñez-Márquez & Julio-César Salgado-Ramírez, 2021. "Classification of Diseases Using Machine Learning Algorithms: A Comparative Study," Mathematics, MDPI, vol. 9(15), pages 1-21, July.
  41. Gao, Sujuan & Shen, Jianzhao, 2007. "Asymptotic properties of a double penalized maximum likelihood estimator in logistic regression," Statistics & Probability Letters, Elsevier, vol. 77(9), pages 925-930, May.
  42. Zachary J Ward & Sara N Bleich & Michael W Long & Steven L Gortmaker, 2021. "Association of body mass index with health care expenditures in the United States by age and sex," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-10, March.
  43. Wang, Shenhao & Mo, Baichuan & Zheng, Yunhan & Hess, Stephane & Zhao, Jinhua, 2024. "Comparing hundreds of machine learning and discrete choice models for travel demand modeling: An empirical benchmark," Transportation Research Part B: Methodological, Elsevier, vol. 190(C).
  44. Kakourou Alexia & Vach Werner & Nicolardi Simone & van der Burgt Yuri & Mertens Bart, 2016. "Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(5), pages 415-430, October.
  45. Iqbal H. Sarker, 2023. "Machine Learning for Intelligent Data Analysis and Automation in Cybersecurity: Current and Future Prospects," Annals of Data Science, Springer, vol. 10(6), pages 1473-1498, December.
  46. Laura Vicente-Gonzalez & Jose Luis Vicente-Villardon, 2022. "Partial Least Squares Regression for Binary Responses and Its Associated Biplot Representation," Mathematics, MDPI, vol. 10(15), pages 1-23, July.
  47. repec:wyi:journl:002122 is not listed on IDEAS
  48. Meisam Moghimbeygi & Anahita Nodehi, 2022. "Multinomial Principal Component Logistic Regression on Shape Data," Journal of Classification, Springer;The Classification Society, vol. 39(3), pages 578-599, November.
  49. Wenfa Li & Hongzhe Liu & Peng Yang & Wei Xie, 2016. "Supporting Regularized Logistic Regression Privately and Efficiently," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-19, June.
  50. Chung, Wingyan, 2014. "BizPro: Extracting and categorizing business intelligence factors from textual news articles," International Journal of Information Management, Elsevier, vol. 34(2), pages 272-284.
  51. Kamiar Rahnama Rad & Arian Maleki, 2020. "A scalable estimate of the out‐of‐sample prediction error via approximate leave‐one‐out cross‐validation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 965-996, September.
  52. Julio César Hernández-Sánchez & José Luis Vicente-Villardón, 2017. "Logistic biplot for nominal 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 307-326, June.
  53. N. H. Jadhav, 2020. "On linearized ridge logistic estimator in the presence of multicollinearity," Computational Statistics, Springer, vol. 35(2), pages 667-687, June.
  54. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
  55. Zanin, Luca, 2020. "Combining multiple probability predictions in the presence of class imbalance to discriminate between potential bad and good borrowers in the peer-to-peer lending market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
  56. Heidema A. Geert & Nagelkerke Nico, 2008. "Developing a Discrimination Rule between Breast Cancer Patients and Controls Using Proteomics Mass Spectrometric Data: A Three-Step Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(2), pages 1-11, February.
  57. Christian S Göbl & Latife Bozkurt & Andrea Tura & Giovanni Pacini & Alexandra Kautzky-Willer & Martina Mittlböck, 2015. "Application of Penalized Regression Techniques in Modelling Insulin Sensitivity by Correlated Metabolic Parameters," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-19, November.
  58. Scott D. Bass & Lukasz A. Kurgan, 2010. "Discovery of factors influencing patent value based on machine learning in patents in the field of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 217-241, February.
  59. Najari, Shaghayegh & Salehi, Mostafa & Ranjbar, Vahid & Jalili, Mahdi, 2019. "Link prediction in multiplex networks based on interlayer similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
  60. repec:lan:wpaper:4816 is not listed on IDEAS
  61. G Johnes, 2005. "Nations will fall? Revisiting the economic determinants of attitudes to European integration," Working Papers 566772, Lancaster University Management School, Economics Department.
  62. Li Xu & Zhenxin Zhan & Shouhuai Xu & Keying Ye & Keesook Han & Frank Born, 2013. "Cross-Layer Detection of Malicious Websites," Working Papers 0150mss, College of Business, University of Texas at San Antonio.
  63. Ying Guan & Guang-Hui Fu, 2022. "A Double-Penalized Estimator to Combat Separation and Multicollinearity in Logistic Regression," Mathematics, MDPI, vol. 10(20), pages 1-19, October.
  64. Natalia Pecorari & Jose Cuesta, 2024. "Citizen Participation and Political Trust in Latin America and the Caribbean: A Machine Learning Approach," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 36(5), pages 1227-1252, October.
  65. José-Luis Velázquez-Rodríguez & Yenny Villuendas-Rey & Oscar Camacho-Nieto & Cornelio Yáñez-Márquez, 2020. "A Novel and Simple Mathematical Transform Improves the Perfomance of Lernmatrix in Pattern Classification," Mathematics, MDPI, vol. 8(5), pages 1-46, May.
  66. Jooyeon Jamie Im & Binna Kim & Jaeuk Hwang & Jieun E Kim & Jung Yoon Kim & Sandy Jeong Rhie & Eun Namgung & Ilhyang Kang & Sohyeon Moon & In Kyoon Lyoo & Chang-hyun Park & Sujung Yoon, 2017. "Diagnostic potential of multimodal neuroimaging in posttraumatic stress disorder," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
  67. Ian R. White, 2009. "Multivariate random-effects meta-analysis," Stata Journal, StataCorp LP, vol. 9(1), pages 40-56, March.
  68. Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2020. "Measuring systemic risk in the U.S. Banking system," Economic Modelling, Elsevier, vol. 91(C), pages 646-658.
  69. Sunil Kumar & Ilyoung Chong, 2018. "Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States," IJERPH, MDPI, vol. 15(12), pages 1-24, December.
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  71. Li Shaoyu & Lu Qing & Fu Wenjiang & Romero Roberto & Cui Yuehua, 2009. "A Regularized Regression Approach for Dissecting Genetic Conflicts that Increase Disease Risk in Pregnancy," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-30, October.
  72. Kadri Ulas Akay, 2014. "A graphical evaluation of logistic ridge estimator in mixture experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1217-1232, June.
  73. Tutz, Gerhard & Binder, Harald, 2007. "Boosting ridge regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6044-6059, August.
  74. M Berkan Sesen & Ann E Nicholson & Rene Banares-Alcantara & Timor Kadir & Michael Brady, 2013. "Bayesian Networks for Clinical Decision Support in Lung Cancer Care," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
  75. Faisal M. Zahid & Shahla Ramzan, 2012. "Ordinal ridge regression with categorical predictors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 161-171, March.
  76. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
  77. Rodrigo P. Rocha & Loren Koçillari & Samir Suweis & Michele Filippo De Grazia & Michel Thiebaut Schotten & Marco Zorzi & Maurizio Corbetta, 2022. "Recovery of neural dynamics criticality in personalized whole-brain models of stroke," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
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