A new Jackknifing ridge estimator for logistic regression model

Hammood, Nawal Mahmood; Algamal, Zakariya Yahya

doi:10.22075/ijnaa.2022.5908

اداره چاپ و انتشارات دانشگاه سمنان

تعداد نشریات	21
تعداد شماره‌ها	622
تعداد مقالات	9,157
تعداد مشاهده مقاله	67,485,531
تعداد دریافت فایل اصل مقاله	8,014,972

	A new Jackknifing ridge estimator for logistic regression model
International Journal of Nonlinear Analysis and Applications
مقاله 176، دوره 13، شماره 1، خرداد 2022، صفحه 2127-2135 اصل مقاله (298.99 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.5908
نویسندگان
Nawal Mahmood Hammood^* ¹؛ Zakariya Yahya Algamal²
¹Department of management Information systems, College of Administration and Economics, University of Mosul, Mosul, Iraq.
²Department of Statistics and Informatics, University of Mosul, Mosul, Iraq.
تاریخ دریافت: 15 اردیبهشت 1400، تاریخ پذیرش: 22 مهر 1400
چکیده
In reducing the effects of collinearity, the ridge estimator (RE) has been consistently demonstrated to be an attractive shrinkage method. In application, when the response variable is binary data, the logistic regression model (LRM) is a well-known model. However, it is known that collinearity negatively affects the variance of maximum likelihood estimator of the LRM. To address this problem, a logistic ridge estimator was proposed by several authors. In this work, a Jackknifing logistic ridge estimator (NJLRE) is proposed and derived. The Monte Carlo simulation results recommend that the NJLRE estimator can bring significant improvement relative to other existing estimators. Furthermore, the real application results demonstrate that the NJLRE estimator outperforms both LRE and MLE in terms of predictive performance.
کلیدواژه‌ها
Collinearity؛ Jackknife estimator؛ ridge estimator؛ logistic regression model؛ Monte Carlo simulation

مراجع
[1] Z. Y. Algamal and M. H. Lee, Penalized Poisson Regression Model using adaptive modified Elastic Net Penalty, Electron. J. Appl. Stat. Anal., 8(2)(2015) 236-245. [2] M. Arashi, B. M. G. Kibria and T. Valizade, On ridge parameter estimators under stochastic subspace hypothesis, J. Stat. Comput. Simul., 87(5)(2017) 966–983. [3] Y. Asar and A. Gen¸c, New shrinkage parameters for the Liu-type logistic estimators, Commun. Stat. Simul. Comput., 45(3)(2015) 1094-1103. https://doi.org/10.1080/03610918.2014.995815 [4] F. S. M. Batah, T. V. Ramanathan and S. D. Gore, The efficiency of modefied jackknife and ridge type regression estimators - A comparison, Surv. Math. Appl., 3 (2008) 111 – 122. [5] L. Firinguettia, B. M. G. Kibria and R. Araya, Study of Partial Least Squares and Ridge Regression Methods, Commun Stat. Simul. . Comput., 46(8) (2017) 6631-6644. [6] A. E. Hoerl and R. W. Kennard, Ridge regression: Biased estimation for nonorthogonal problems, Technometrics, 12(1)(1970) 55-67. [7] I. J. Kang, L. W. Wang, S. J. Hsu, C. C. Lee, Y. C. Lee , Y. S. Wu, and J. H. Chern, Design and efficient synthesis of novel arylthiourea derivatives as potent hepatitis C virus inhibitors , Bioorg. Med. Chem. Lett.,19(21)(2009) 6063-6068, https://doi.org/10.1016/j.bmcl.2009.09.037. [8] F. S. M. Batah, T. V. Ramanathan and S. D. Gore, The efficiency of modefied jackknife and ridge type regression estimators - A comparison, Surv. Math. Appl., 3 (2008) 111-122. [9] L. Firinguettia, B. M. G. Kibria and R. Araya, Study of Partial Least Squares and Ridge Regression Methods, Commun, Stat. Simul. and Comput., 46(8)(2017) 6631-6644. [10] A. E. Hoerl and R. W. Kennard, Ridge regression: Biased estimation for nonorthogonal problems, Technometrics, 12(1) (1970) 55-67. [11] I. J. Kang, L. W. Wang, S. J. Hsu, C. C. Lee, Y. C. Lee, Y. S. Wu, and J. H. Chern, Design and efficient synthesis of novel arylthiourea derivatives as potent hepatitis C virus inhibitors, Bioorg. Med. Chem. Lett, 19(21)(2009) 6063-6068, https://doi.org/10.1016/j.bmcl.2009.09.037. [12] I. J. Kang, L. W. Wang, C. C. Lee, Y. C. Lee, Chao, Y. S. Hsu, T. A. Hsu and J. H. Chern, Design, synthesis, and anti-HCV activity of thiourea compounds, Bioorg. Med. Chem. Lett. 19(7) (2009) 1950-1955. https://doi. org/10.1016/j.bmcl.2009.02.048 [13] I. J. Kang, L. W. Wang, T. K. Yeh , C. C. Lee, Y. C. Lee, S. J. Hsu,and J. H. Chern, Synthesis, activity, and pharmacokinetic properties of a series of conformationally-restricted thiourea analogs as novel hepatitis C virus inhibitors, Bioorg. Med. Chem., 18(17) (2010) 6414-6421. https://doi.org/10.1016/j.bmc.2010.07.002 [14] N. Khatri, V. Lather and A. K. Madan, Diverse classification models for anti-hepatitis C virus activity of thiourea derivatives, Chemom. Intell. Lab. Syst. , 140(2015) 13-21. https://doi.org/10.1016/j.chemolab.2014.10.007 [15] M. Khurana, Y. P. Chaubey and S. Chandra, Jackknifing the ridge regression estimator: A revisit, Communications in Statistics-Theory and Methods, 43(24)(2014) 5249-5262. [16] B. M. G. Kibria, Performance of some new ridge regression estimators, Commun. Stat. Simul. Comput., 32(2)(2003) 419-435. https://doi.org/10.1081/SAC-120017499 [17] B. M. G. Kibria, K. Mansson and G. Shukur, A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression, Commun. Stat. Simul. Comput., 44(4)(2015) 943-957, https://doi.org/10. 1080/03610918.2013.796981. [18] S. Le Cessie and J. C. Van Houwelingen, Ridge estimators in logistic regression, J. R. Stat. Soc.: Ser. C (Applied Statistics), 41(1)(1992) 191-201. [19] A. Lee and M. Silvapulle, Ridge estimation in logistic regression, Commun. Stat. Simul. Comput., 17(4)(1988) 1231-1257. [20] K. Mansson and G. Shukur, A Poisson ridge regression estimator, Econ. Modell., 28(4)(2011) 1475-1481. https: //doi.org/10.1016/j.econmod.2011.02.030. [21] D. C. Montgomery, E. A. Peck and G. G. Vining, Introduction to linear regression analysis, New York: John Wiley & Sons, 2015. [22] H. Nyquist, Applications of the jackknife procedure in ridge regression, Comput. Stat. . Data Anal., 6(2)(1988), 177-183. [23] M. R. OzkaleckkniA ja fed ridge estimator in the linear regression model with heteroscedastic or correlated errors, Stat. Probab. Lett., 78(18)(2008) 3159-3169, https://doi.org/10.1016/j.spl.2008.05.039. [24] N. K. Rashad and Z. Y. Algamal, A New Ridge Estimator for the Poisson Regression Model, Iran. J. Sci. Technol., Trans. A: Sci., https://doi.org/10.1007/s40995-019-00769-3. [25] A. K. M. E. Saleh, M. Arashi and B. M. G. Kibria, Theory of Ridge Regression Estimation with Applications, New York: Wiley, 2019 .[26] A. K. M. E. Saleh and B. M. G. Kibria, Improved ridge regression estimators for the logistic regression model, Comput. Stat., 28(6)(2012) , 2519-2558. [27] B. Singh, Y. P. Chaubey and T. D. Dwivedi An almost unbiased ridge estimator, Sankhy¯a: Indian J. Stat. Ser. B, (1986) 342-346.
آمار تعداد مشاهده مقاله: 15,875 تعداد دریافت فایل اصل مقاله: 686

سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب

پیوندهای مفید

پیوندهای مفید

آمار

A new Jackknifing ridge estimator for logistic regression model