Using the Spatial Autoregressive Model to Study the Effect of Some Variables on the Mean

Authors

  • Jinan Abdullah Anber Baghdad Technical College of Management, Dep. of Financial and Banking Sciences Techniques, Middle Technical University, Baghdad, Iraq Author https://orcid.org/0000-0003-2377-9128
  • Ghiath Hameed Majeed College of Basic Education, Dep. of Mathematics, Mustansiriyah University, Baghdad, Iraq Author https://orcid.org/0000-0001-7802-9477
  • Mohammed Qadoury Abed Al-Mansour University College, Dep. of Accounting & Banking Science, Baghdad, Iraq Author https://orcid.org/0000-0001-5758-1369
  • Wadhah S. Ibrahim College of Management and Economics, Dep. of Statistic, Mustansiriyah University, Baghdad, Iraq Author https://orcid.org/0000-0003-1781-9621

DOI:

https://doi.org/10.62933/ns1nxx54

Keywords:

Spatial Autoregressive Model , Maximum likelihood method , Rook Contiguity Criterion , Hemoglobin

Abstract

Spatial estimation methods have shown their effectiveness in finding appropriate solutions that researchers encounter with regression models. In this research, the effect of some variables on hemoglobin will be studied at the level of Iraqi regions and. The maximum likelihood method will be used to estimate the spatial autoregressive model under the Rook contiguity spatial adjacency matrix. It has shown that the average hemoglobin data suffers from spatial dependence and that the variables (white blood cells, platelets, blood viscosity) have an effect on hemoglobin diseases.

References

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[2] Akkar, A. A., Anber, J. A., & Ibrahim, W. S. (2023). The Study of Spatial Effect on Some Variables of Water Pollution in Baghdad Regions. Al-Rafidain University College For Sciences, (54).‏

[3] Anselin, L. (1992)"Spatial Data Analysis With GIS: An Introduction to Appalachian the Social Sciences", National Center for Geographic Information and Analysis, University of California, Santa Barbara, CA 93106.

[4] Anselin, L. (2010). Thirty years of spatial econometrics. Papers in regional science, 89(1), 3-26.

[5] Anselin, L. (2013). Spatial econometrics: methods and models (Vol. 4). Springer Science & Business Media.‏

[6] Ibrahim, W. S., Majeedb, G. H., & Hussain, W. J. (2021). Comparison and estimation of a Spatial Autoregressive (SAR) model for cancer in Baghdad Regions. Int. J. Agricult. Stat. Sci. Vol, 17(1), 1921-1927.‏

[7] Ibrahim, W. S., & Mousa, N. S. (2022). Estimation of the general spatial regression model (SAC) by the maximum likelihood method. International Journal of Nonlinear Analysis and Applications, 13(1), 2947-2957.‏

[8] Ibrahim, W. S., & Mousa, N. S. (2022). Estimation of the parameters of the spatial general regression model (SAC) by the method of the greatest possibility (MLE) of the adjacency matrix using simulation. journal of the college of basic education, 28(114/علمي).‏

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Published

2025-05-11

Issue

Vol. 2 No. special issue for ICSA2025 (2025)

Section

Original Articles

License

Copyright (c) 2025 Jinan Abdullah Anber, Ghiath Hameed Majeed, Mohammed Qadoury Abed, Wadhah S. Ibrahim (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Licensed under a CC-BY license: https://creativecommons.org/licenses/by-nc-sa/4.0/

How to Cite

Using the Spatial Autoregressive Model to Study the Effect of Some Variables on the Mean. (2025). Iraqi Statisticians Journal, 2(special issue for ICSA2025), 158-163. https://doi.org/10.62933/ns1nxx54