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Original Articles

Combining ridge and principal component regression:a money demand illustration

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Pages 197-205 | Published online: 27 Jun 2007

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Hongmei Chen, Jibo Wu & B. M. Golam Kibria. (2023) Further research on the modified ridge principal component estimator in linear model. Communications in Statistics - Theory and Methods 52:24, pages 8894-8901.
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Muhammad Nauman Akram, Muhammad Amin, Adewale F. Lukman & Saima Afzal. (2022) Principal component ridge type estimator for the inverse Gaussian regression model. Journal of Statistical Computation and Simulation 92:10, pages 2060-2089.
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Saman Babaie-Kafaki & Mahdi Roozbeh. (2017) A revised Cholesky decomposition to combat multicollinearity in multiple regression models. Journal of Statistical Computation and Simulation 87:12, pages 2298-2308.
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Issam Dawoud & Selahattin Kaçıranlar. (2017) Evaluation of the predictive performance of the r-k and r-d class estimators. Communications in Statistics - Theory and Methods 46:8, pages 4031-4050.
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Daojiang He, Yan Wu & Kai Xu. (2016) A Class of s–K Type Principal Components Estimators in the Linear Model. Communications in Statistics - Simulation and Computation 45:8, pages 2709-2719.
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Jibo Wu. (2016) On the predictive performance of the almost unbiased Liu estimator. Communications in Statistics - Theory and Methods 45:17, pages 5193-5203.
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Jibo Wu. (2016) Superiority of the r-k class estimator over some estimators in a misspecified linear model. Communications in Statistics - Theory and Methods 45:5, pages 1453-1458.
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M. Revan Özkale & Engin Arıcan. (2016) A new biased estimator in logistic regression model. Statistics 50:2, pages 233-253.
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Hu Yang & Jiewu Huang. (2016) Further research on the principal component two-parameter estimator in linear model. Communications in Statistics - Theory and Methods 45:3, pages 566-576.
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Gülesen Üstündaĝ Şiray. (2015) r-d Class Estimator Under Misspecification. Communications in Statistics - Theory and Methods 44:22, pages 4742-4756.
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Jibo Wu & Hu Yang. (2015) On the Principal Component Liu-type Estimator in Linear Regression. Communications in Statistics - Simulation and Computation 44:8, pages 2061-2072.
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Gülesen Üstündağ Şiray. (2014) Modified and Restricted r-k Class Estimators. Communications in Statistics - Theory and Methods 43:24, pages 5130-5155.
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Fei-Bao Liang & Yi-Xin Lan. (2014) A Generalized Diagonal Ridge-type Estimator in Linear Regression. Communications in Statistics - Theory and Methods 43:6, pages 1145-1163.
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Jibo Wu & Hu Yang. (2014) On the Stochastic Restricted Almost Unbiased Estimators in Linear Regression Model. Communications in Statistics - Simulation and Computation 43:2, pages 428-440.
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Mustafa Ismaeel Alheety & B.M. Golam Kibria. (2013) Modified Liu-Type Estimator Based on (r − k) Class Estimator. Communications in Statistics - Theory and Methods 42:2, pages 304-319.
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Edward Santos & Erniel Barrios. (2012) Nonparametric Decomposition of Time Series Data with Inputs. Communications in Statistics - Simulation and Computation 41:9, pages 1693-1710.
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Gülesen Üstündaǧ Şiray & Sadullah Sakallıoǧlu. (2012) Superiority of the r–k Class Estimator Over Some Estimators In A Linear Model. Communications in Statistics - Theory and Methods 41:15, pages 2819-2832.
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M. Revan Özkale. (2012) Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators. Journal of Statistical Computation and Simulation 82:5, pages 653-688.
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Jianwen Xu & Hu Yang. (2011) On the restricted r–k class estimator and the restricted r–d class estimator in linear regression. Journal of Statistical Computation and Simulation 81:6, pages 679-691.
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Jianwen Xu & Hu Yang. (2011) On the restricted almost unbiased estimators in linear regression. Journal of Applied Statistics 38:3, pages 605-617.
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Feras Sh. M. Batah, M. Revan Özkale & S. D. Gore. (2009) Combining Unbiased Ridge and Principal Component Regression Estimators. Communications in Statistics - Theory and Methods 38:13, pages 2201-2209.
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Danaipong Chetchotsak & Janet M. Twomey. (2007) Combining neural networks for function approximation under conditions of sparse data: the biased regression approach. International Journal of General Systems 36:4, pages 479-499.
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M. Revan Özkale & Selahattin Kaçiranlar. (2007) Comparisons of the Unbiased Ridge Estimation to the Other Estimations. Communications in Statistics - Theory and Methods 36:4, pages 707-723.
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José Raúl Martinez, AV Valparaísoy & R. Martínez. (1990) An optimal property of the “(r,k ) class estimators”. Communications in Statistics - Theory and Methods 19:4, pages 1281-1289.
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Ehsan S. Soofi. (1988) Principal component regression under exchangeability. Communications in Statistics - Theory and Methods 17:6, pages 1717-1733.
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Masuo Nomura & Tsuneharu Ohkubo. (1985) A note on combining ridge and principal component regression. Communications in Statistics - Theory and Methods 14:10, pages 2489-2493.
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Dan Huang, Jiewu Huang & Dewei Bai. Combination of the modified Kibria–Lukman and the principal component regression estimators. Communications in Statistics - Simulation and Computation 0:0, pages 1-16.
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Rasha A. Farghali, Adewale F. Lukman & Ayodeji Ogunleye. Enhancing model predictions through the fusion of stein estimator and principal component regression. Journal of Statistical Computation and Simulation 0:0, pages 1-16.
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Articles from other publishers (43)

Adewale F. Lukman, Emmanuel T. Adewuyi, Ohud A. Alqasem, Mohammad Arashi & Kayode Ayinde. (2024) Enhanced Model Predictions through Principal Components and Average Least Squares-Centered Penalized Regression. Symmetry 16:4, pages 469.
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Ulduz Mammadova & M. Revan Özkale. (2023) Detecting shifts in Conway–Maxwell–Poisson profile with deviance residual-based CUSUM and EWMA charts under multicollinearity. Statistical Papers 65:2, pages 597-643.
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Ulduz Mammadova. (2024) CONWAY-MAXWELL-POISSON PROFILE MONITORING WITH RK-SHEWHART CONTROL CHART: A COMPARATIVE STUDY. Journal of Scientific Reports-A.
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Antoine Godichon-Baggioni, Wei Lu & Bruno Portier. (2024) Recursive ridge regression using second-order stochastic algorithms. Computational Statistics & Data Analysis 190, pages 107854.
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Idowu J. I., Owolabi A. T., Oladapo O. J., Ayinde K., Oshuoporu O. A. & Alao A. N.. (2023) Mitigating Multicollinearity in Linear Regression Model with Two Parameter Kibria-Lukman Estimators. WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 18, pages 612-635.
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A. F. Lukman, M. Norouzirad, F. J. Marques & D. Mazarei. (2023) Combining Kibria-Lukman and principal component estimators for the distributed lag models. Behaviormetrika 50:2, pages 621-652.
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K.C. Arum, F.I. Ugwuowo, H.E. Oranye, T.O. Alakija, T.E. Ugah & O.C. Asogwa. (2023) Combating outliers and multicollinearity in linear regression model using robust Kibria-Lukman mixed with principal component estimator, simulation and computation. Scientific African 19, pages e01566.
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Hongmei Chen & Jibo Wu. (2022) On the mixed Kibria–Lukman estimator for the linear regression model. Scientific Reports 12:1.
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Gargi Tyagi & Shalini Chandra. (2022) A general restricted estimator in binary logistic regression in the presence of multicollinearity. Brazilian Journal of Probability and Statistics 36:2.
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Kingsley Chinedu Arum & Fidelis Ifeanyi Ugwuowo. (2022) Combining principal component and robust ridge estimators in linear regression model with multicollinearity and outlier. Concurrency and Computation: Practice and Experience 34:10.
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Selahattin Kaçıranlar, Nimet Özbay, Ecem Özkan & Hüseyin Güler. (2021) Comparison of Liu and two parameter principal component estimator to combat multicollinearity. Concurrency and Computation: Practice and Experience 34:5.
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Özge Kuran. (2021) The 𝑟-𝑑 class predictions in linear mixed models. Journal of Inverse and Ill-posed Problems 29:4, pages 477-498.
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Atıf ABBASI & Revan ÖZKALE. (2021) The r-k class estimator in generalized linear models applicable with simulation and empirical study using a Poisson and Gamma responses. Hacettepe Journal of Mathematics and Statistics 50:2, pages 594-611.
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Yuanhan Li, Jerome P. Keating & Narayanaswamy Balakrishnan. (2021) PMC Theorems on PCR–Ridge Class Estimators. Journal of Statistical Theory and Practice 15:1.
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Mahdi Roozbeh, Saman Babaie–Kafaki & Zohre Aminifard. (2021) Two penalized mixed–integer nonlinear programming approaches to tackle multicollinearity and outliers effects in linear regression models. Journal of Industrial & Management Optimization 17:6, pages 3475.
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Mustafa Nadhim Lattef & Mustafa Ismaeel Naif. (2020) STUDY OF SOME KINDS OF ALMOST UNBIASED ESTIMATOR AND PRINCIPLE COMPONENT ESTIMATOR FOR REGRESSION MODEL. Journal of Physics: Conference Series 1664:1, pages 012036.
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Adewale F. Lukman, Kayode Ayinde, Olajumoke Oludoun & Clement A. Onate. (2020) Combining modified ridge-type and principal component regression estimators. Scientific African 9, pages e00536.
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Nilgün Yıldız. 2020. Statistical Methodologies. Statistical Methodologies.
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Yalian Li & Hu Yang. (2016) Performance of the restricted almost unbiased type principal components estimators in linear regression model. Statistical Papers 60:1, pages 19-34.
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Mahdi Roozbeh, Saman Babaie-Kafaki & Alireza Naeimi Sadigh. (2018) A heuristic approach to combat multicollinearity in least trimmed squares regression analysis. Applied Mathematical Modelling 57, pages 105-120.
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Mahdi Roozbeh. (2018) Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion. Computational Statistics & Data Analysis 117, pages 45-61.
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Shalini Chandra & Gargi Tyagi. (2017) On the Performance of Some Biased Estimators in a Misspecified Model with Correlated Regressors. Statistics in Transition New Series 18:1, pages 27-52.
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Manickavasagar Kayanan & Pushpakanthie Wijekoon. (2017) Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model. Open Journal of Statistics 07:05, pages 876-900.
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Gargi Tyagi & Shalini Chandra. (2017) A Note on the Performance of Biased Estimators with Autocorrelated Errors. International Journal of Mathematics and Mathematical Sciences 2017, pages 1-12.
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Mahdi Roozbeh, Saman Babaie-Kafaki & Mohammad Arashi. (2016) A class of biased estimators based on QR decomposition. Linear Algebra and its Applications 508, pages 190-205.
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Shalini Chandra & Nityananda Sarkar. (2015) A restricted $$r{-}k$$ r - k class estimator in the mixed regression model with autocorrelated disturbances. Statistical Papers 57:2, pages 429-449.
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Shalini Chandra & Nityananda Sarkar. (2015) Comparison of the r- (k, d) class estimator with some estimators for multicollinearity under the Mahalanobis loss function. International Econometric Review 7:1, pages 1-12.
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Jiewu Huang & Hu Yang. (2013) On a principal component two-parameter estimator in linear model with autocorrelated errors. Statistical Papers 56:1, pages 217-230.
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Deniz Inan. (2013) Combining the Liu-type estimator and the principal component regression estimator. Statistical Papers 56:1, pages 147-156.
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Gülesen Üstündagˇ Şiray, Selahattin Kaçıranlar & Sadullah Sakallıoğlu. (2012) r − k Class estimator in the linear regression model with correlated errors. Statistical Papers 55:2, pages 393-407.
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Jibo Wu. (2014) Comparison of Some Estimators under the Pitman’s Closeness Criterion in Linear Regression Model. Journal of Applied Mathematics 2014, pages 1-6.
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Yalian Li & Hu Yang. (2014) Two Classes of Almost Unbiased Type Principal Component Estimators in Linear Regression Model. Journal of Applied Mathematics 2014, pages 1-6.
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Jibo Wu. (2014) On the Stochastic Restricted Class Estimator and Stochastic Restricted Class Estimator in Linear Regression Model . Journal of Applied Mathematics 2014, pages 1-6.
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Chaolin Liu, Hu Yang & Jibo Wu. (2013) On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression. Journal of Applied Mathematics 2013, pages 1-10.
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Jibo Wu. (2013) On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion. Journal of Applied Mathematics 2013, pages 1-7.
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M. Revan Özkale & Selahattin Kaçıranlar. (2007) Superiority of the class estimator over some estimators by the mean square error matrix criterion. Statistics & Probability Letters 77:4, pages 438-446.
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