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Research Article

A restricted gamma ridge regression estimator combining the gamma ridge regression and the restricted maximum likelihood methods of estimation

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 1696-1713 | Received 03 Aug 2021, Accepted 08 Nov 2021, Published online: 27 Nov 2021

References

  • Algamal ZY. Developing a ridge estimator for the gamma regression model. J Chemometr. 2018;32(10):e3054.
  • Qasim M, Amin M, Amanullah M. On the performance of some new Liu parameters for the gamma regression model. J Stat Comput Simul. 2018;88(16):3065–3080.
  • Nyquist H. Restricted estimation of generalized linear models. J Royal Statist Soc C Appl Statist. 1991;40(1):133–141.
  • Kibria BG, Saleh AME. Improving the estimators of the parameters of a probit regression model: a ridge regression approach. J Stat Plan Inference. 2012;142(6):1421–1435.
  • Qasim M, Kibria BMG, Månsson K, et al. A new Poisson Liu regression estimator: method and application. J Appl Stat. 2020;47(12):2258–2271.
  • Hoerl AE, Kennard RW. Ridge regression: biased estimation for nonorthogonal problems. Technometrics. 1970;12:55–67.
  • Amin M, Qasim M, Amanullah M, et al. Performance of some ridge estimators for the gamma regression model. Statist Papers. 2020;61(3):997–1026.
  • Kaçiranlar S, Sakallioğlu S, Akdeniz F, et al. A new biased estimator in linear regression and a detailed analysis of the widely-analyzed dataset on portland cement. Sankhyā Ind J Stat B. 1999: 443–459.
  • Sarkar N. A new estimator combining the ridge regression and the restricted least squares methods of estimation. Commun Stat Theory Methods. 1992;21(7):1987–2000.
  • Mahmoudi A, Arabi Belaghi R, Mandal S. A comparison of preliminary test, stein-type and penalty estimators in gamma regression model. J Stat Comput Simul. 2020;90(17):3051–3079.
  • Månsson K, Kibria BM, Shukur G. A restricted Liu estimator for binary regression models and its application to an applied demand system. J Appl Stat. 2016;43(6):1119–1127.
  • Asar Y, Arashi M, Wu J. Restricted ridge estimator in the logistic regression model. Commun Stat Simul Comput. 2017;46(8):6538–6544.
  • Segerstedt B. On ordinary ridge regression in generalized linear models. Commun Statist Theory Methods. 1992;21(8):2227–2246.
  • Kurtoğlu F, Özkale MR. Restricted ridge estimator in generalized linear models: Monte Carlo simulation studies on Poisson and binomial distributed responses. Commun Stat Simul Comput. 2017;48(4):1191–1218.
  • Wang SG, Wu MX, Jia ZZ. Matrix inequalities. 2nd ed Beijing: Chinese Science Press; 2006.
  • Rao CR, Toutenburg H, Shalabh, et al. Linear models and generalizations—least squares and alternatives. Berlin: Springer; 2008.
  • Kibria BG. Performance of some new ridge regression estimators. Commun Stat Simul Comput. 2003;32(2):419–435.
  • Qasim M, Månsson K, Kibria BMG. On some beta ridge regression estimators: method, simulation and application. J Stat Comput Simul. 2021;91(9):1699–1712.
  • McDonald GC, Galarneau DI. A Monte Carlo evaluation of some ridge-type estimators. J Am Stat Assoc. 1975;70(350):407–416.
  • Månsson G K, Shukur G. A Poisson ridge regression estimator. Econo Model. 2011;28:1475–1481.
  • Varathan N, Wijekoon P. Optimal generalized logistic estimator. Commun Stat Theory Methods. 2018;47:463–474.
  • Weisberg S. Applied linear regression. John Wiley & Sons; 1980.
  • J. Zhang, Powerful goodness-of-fit and multi-sample tests, PhD Thesis. 2011. York University, Toronto.
  • Evan DL, Drew JH, Leemis LM. The distribution of Kolmogorov–Smirnov, Cramer–von Mises, and Anderson–Darling test statistics for exponential populations with estimated parameters. Commun Stat Theory Methods. 2008;37:1396–1421.