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Comparison of Several Parameter Estimation Methods in Overcoming Multicollinearity in the Model Poisson Inverse Gaussian (Case Study:HIV)


Authors : Desfita Ratna Enjeli; Netti Herawati; Agus Sutrisno; Subian Saidi; Misgiyati

Volume/Issue : Volume 11 - 2026, Issue 7 - July


Google Scholar : https://tinyurl.com/7usc9yb8

Scribd : https://tinyurl.com/ej99e2u8

DOI : https://doi.org/10.38124/ijisrt/26jul414

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Abstract : New Improved Liu-Type Estimator (P-IGNLTE) in handling multicollinearity problems [3][4]. The data used in this study consist of HIV case data from 27 regencies/cities in West Java Province in 2023 obtained from Badan Pusat Statistik Provinsi Jawa Barat [5]. The independent variables include the percentage of the poor population, the number of condom users, the number of health workers, the number of health facilities, the number of injectable contraceptive users, population size, and population density. The best model was selected based on the smallest Mean Square Error (MSE) value.

Keywords : Poisson Inverse Gaussian; Multicollinearity; PIGML; PIGRE; PIGLE; PIGLTE; PIGNLTE; Mean Square Error.

References :

  1. Centers for Disease Control and Prevention, “About HIV,” Atlanta, GA, USA, 2024.
  2. A. Colin Cameron and Pravin K. Trivedi, Regression Analysis of Count Data, 2nd ed. Cambridge, United Kingdom: Cambridge University Press, 2013, ch. 4.
  3. Herindrawati, A. Y., I. N. Latra, and Purhadi, “Pemodelan Regresi Poisson Inverse Gaussian Studi Kasus: Jumlah Kasus Baru HIV di Provinsi Jawa Tengah Tahun 2015,” Jurnal Sains dan Seni ITS, vol. 6, no. 1, pp. D143–D148, 2017.
  4. A. Alghamdi, F. Almulhim, and H. Alrweili, “Poisson Inverse Gaussian New Improved Liu-Type Estimator under Multicollinearity,” Communications in Statistics – Simulation and Computation, vol. 54, no. 2, pp. 1–18, 2025.
  5. Badan Pusat Statistik Provinsi Jawa Barat, “Jumlah Kasus HIV/AIDS Menurut Kabupaten/Kota di Provinsi Jawa Barat Tahun 2023,” 2024.
  6. McCullagh, P., and J. A. Nelder, Generalized Linear Models, 2nd ed. London, United Kingdom: Chapman and Hall, 1989.
  7. N. T. Yulinda, Supriyanto, and B. H. Guswanto, “Penerapan Metode Jackknife Ridge Regression untuk Mengatasi Multikolinearitas (Studi Kasus: Kemiskinan di Provinsi Jawa Tengah),” Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP), vol. 17, no. 1, pp. 73–86, 2025.
  8. Arthur E. Hoerl and Robert W. Kennard, “Ridge Regression: Biased Estimation for Nonorthogonal Problems,” Technometrics, vol. 12, no. 1, pp. 55–67, 1970.
  9. A. Batool, M. Amin, and A. Elhassanein, “On the Performance of Some New Ridge Parameter Estimators in the Poisson-Inverse Gaussian Ridge Regression,” Alexandria Engineering Journal, vol. 70, no. 1, pp. 231–245, 2023.
  10. Kejian Liu, “A New Class of Biased Estimate in Linear Regression,” Communications in Statistics - Theory and Methods, vol. 22, no. 2, pp. 393–402, 1993.
  11. M. N. Akram, M. Amin, and M. Qasim, “A New Liu-Type Estimator for the Inverse Gaussian Regression Model,” Journal of Statistical Computation and Simulation, vol. 90, no. 7, pp. 1153–1172, 2020.

New Improved Liu-Type Estimator (P-IGNLTE) in handling multicollinearity problems [3][4]. The data used in this study consist of HIV case data from 27 regencies/cities in West Java Province in 2023 obtained from Badan Pusat Statistik Provinsi Jawa Barat [5]. The independent variables include the percentage of the poor population, the number of condom users, the number of health workers, the number of health facilities, the number of injectable contraceptive users, population size, and population density. The best model was selected based on the smallest Mean Square Error (MSE) value.

Keywords : Poisson Inverse Gaussian; Multicollinearity; PIGML; PIGRE; PIGLE; PIGLTE; PIGNLTE; Mean Square Error.

Paper Submission Last Date
31 - July - 2026

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