A graphical evaluation of logistic ridge estimator in mixture experiments
Author
Abstract
Suggested Citation
DOI: 10.1080/02664763.2013.864261
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- G. Geoffrey Vining & John A. Cornell & Raymond H. Myers, 1993. "A Graphical Approach for Evaluating Mixture Designs," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(1), pages 127-138, March.
- Kadri Ulas Akay & Müjgan Tez, 2011. "Alternative modeling techniques for the quantal response data in mixture experiments," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2597-2616, January.
- Robinson, Kevin S. & Khuri, Andre I., 2003. "Quantile dispersion graphs for evaluating and comparing designs for logistic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 43(1), pages 47-62, May.
- S. le Cessie & J. C. van Houwelingen, 1992. "Ridge Estimators in Logistic Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 191-201, March.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- 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.
- 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.
- 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.
- Eweama, A.U. & Nwosu, J.N. & Owuamanam, C.I. & Obeleagu, S.O, 2021. "Modelling and optimization of proximate and anti-nutritional composition of breakfast cereals produced from blends of millet, mungbean and tigernut flour using response surface methodology," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(8), pages 103-118, August.
- 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.
- Florentin Butaru & QingQing Chen & Brian Clark & Sanmay Das & Andrew W. Lo & Akhtar Siddique, 2015. "Risk and Risk Management in the Credit Card Industry," NBER Working Papers 21305, National Bureau of Economic Research, Inc.
- 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.
- 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.
- Paolo Cimbali & Marco De Leonardis & Alessio Fiume & Barbara La Ganga & Luciana Meoli & Marco Orlandi, 2022. "A decision-making rule to detect insufficient data quality: an application of statistical learning techniques to the non-performing loans banking data?," Questioni di Economia e Finanza (Occasional Papers) 666, Bank of Italy, Economic Research and International Relations Area.
- 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.
- 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.
- 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.
- Elemuo, Godswill Kodili & Obasi, Nneoma Elechi, 2022. "Evaluation and Optimization of the Physical and Sensory Properties of Enhanced Bread Produced From Wheat Flour and Chemically Modified African Yam Bean and Cassava Starches," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 9(4), pages 110-123, April.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:41:y:2014:i:6:p:1217-1232. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.