Dr. Omar Mohammad Barakat Eidous

Professor
Department of Statistics, Faculty of Science, Yarmouk University (YU), Irbid, Jordan

Highest Degree
Ph.D. in Statistics from National University of Malaysia, Malaysia

My URL
https://livedna.org/962.21411

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Area of Interest:

Mathematics
Statistical Inference
Estimation Theory
Mathematical Modelling
Computational Mathematics

Selected Publications

  1. Hanandeh, A. and O.M. Eidous, 2022. Some improvements for existing simple approximations of the normal distribution function. Pak. J Stat. Oper. Res., 18: 555-559.
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  2. Eidous, O.M. and S.A.D.A. AL-Talafha, 2022. Kernel method for overlapping coefficients estimation. Commun. Stat.- Simul. Comput., 51: 5139-5156.
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  3. Eidous, O.M. and E. Ananbeh, 2022. Approximations for cumulative distribution function of standard normal. J. Stat. Manage. Syst., 25: 541-547.
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  4. Eidous, O. and S. Al-Daradkeh, 2022. Estimation of matusita overlapping coefficient for pair normal distributions. Jordan J. Math. Stat. 10.48550/arXiv.2205.06778 Focus to learn more.
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  5. Alodat, M.T., M. Al Fayez and O. Eidous, 2022. On the asymptotic distribution of Matusita's overlapping measure. Commun. Stat.- Theory Methods, 51: 6963-6977.
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  6. Hanandeh, A. and O. Eidous, 2021. A new one-term approximation to the standard normal distribution. Pak. J. Stat. Oper. Res., 17: 381-385.
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  7. Eidous, O. and J. Abu-Hawwas, 2021. An accurate approximation for the standard normal distribution function. J. Inf. Optim. Sci., 42: 17-27.
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  8. Ebrahem, M.H.A.H., N. Al-Momani and O. Eidous, 2021. Variable scale kernel density estimation for simple linear degradation model. Electro. J. Appl. Stat. Anal., 14: 359-372.
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  9. Eidous, O.M. and R. Abu-Shareefa, 2020. New approximations for standard normal distribution function. Commun. Stat Theory Methods, 49: 1357-1374.
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  10. Albadareen, B.I., N. Ismail, O.M. Eidous and J.J. Jaber, 2020. A non-parametric density estimate adaptation for population abundance when the shoulder condition is violated. Electron. J. Appl. Stat. Anal., 13: 562-579.
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  11. Eidous, O. and F. Al-Eibood, 2018. A bias-corrected histogram estimator for line transect sampling. Commun. Stat. Theory Methods, 47: 3675-3686.
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  12. Edous, M. and O. Eidous, 2018. A simple approximation for normal distribution function. Math. Stat., 6: 47-49.
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  13. Al-Bassam, M. and O. Eidous, 2018. Fourth-order kernel method for population density estimation. Far East J. Appl. Math., 98: 31-50.
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  14. Al-Bassam, M. and O. Eidous, 2018. Combination of parametric and nonparametric estimators for population abundance using line transect sampling. J. Inf. Optim. Sci., 39: 1449-1462.
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  15. Dakhn, L.N.B., M.A.H. Ebrahem and O. Eidous, 2017. Semi-parametric method to estimate the time-to-failure distribution and its percentiles for simple linear degradation model. J. Mod. App. Stat. Meth., 16: 322-346.
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  16. Al-Eibood, F. and O. Eidous, 2017. A weighted exponential model for grouped line transect data. Math. Stat., 5: 1-4.
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  17. Eidous, O. and S. Al-Salaman, 2016. One-term approximation for normal distribution function. Math. Stat., 4: 15-18.
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  18. Arif, O.H. and O. Eidous, 2016. Fourth-order kernel method for simple linear degradation model. Commun. Stat.-Simul. Comput., 10.1080/03610918.2016.1186183.
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  19. Al-Eibood, F. and O. Eidous, 2016. A weighted half-normal model for line transect sampling. Int. J. Math. Stat., 17: 14-22.

  20. Eidous, O.M., 2015. Nonparametric estimation of f(0) applying line transect data with and without the shoulder condition. J. Inform. Optim. Sci., 36: 301-315.
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  21. Eidous, O. and F. Al-Eibood, 2015. A new parametric detection function for line transect sampling. J. Fundam. Applied Stat., 8: 1-16.

  22. Eidous, O., 2014. Histogram model with plausible parametric detection function for line transect data. Commun. Stat.-Theory Methods, 43: 1-12.
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  23. Eidous, O. and S. Al-Salman, 2013. Akaike information criterion to select the parametric detection function for kernel estimator using line transect data. J. Modern Applied Stat. Methods, 12: 344-357.
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  24. Eidous, O. and A. Al-Momani, 2013. Estimation of population density based on line transect data with and without the shoulder condition. Eur. Scient. J., 9: 106-118.
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  25. Eidous, O.M., 2012. A new kernel estimator for abundance using line transect sampling without the shoulder condition. J. Korean Stat. Soc., 41: 267-275.
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  26. Eidous, O., 2012. A semi-parametric model for line transect sampling without the shoulder condition. J. Applied Probability Stat., 7: 69-78.

  27. Eidous, O. and M.K. Shakhatreh, 2012. Double kernel method using line transect sampling. Aust. J. Stat., 41: 95-103.
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  28. Ababneh, F. and O.M. Eidous, 2012. A weighted exponential detection function model for line transect data. J. Modern Applied Stat. Methods, 11: 144-151.
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  29. Eidous, O.M., 2011. Additive histogram frequency estimator for wildlife abundance using line transect data without the shoulder condition. Metron, 69: 119-128.
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  30. Eidous, O., 2011. Variable location kernel method using line transect sampling. Environmetrics, 22: 431-440.
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  31. Eidous, O. and M.K. Shakhatreh, 2011. Asymptotic unbiased kernel estimator for line transect sampling. Commun. Stat.-Theory Methods, 40: 4353-4363.
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  32. Eidous, O.M., M.A.A.S. Marie and M.H.B.A. Ebrahem, 2010. A comparative study for bandwidth selection in kernel density estimation. J. Modern Applied Stat. Methods, 9: 263-273.

  33. Eidous, O.M. and A.A. Al-Masri, 2010. Fourth-order kernel method using line transect sampling. Adv. Applic. Stat., 19: 65-79.

  34. Al-Nasser, A.D., O.M. Eidous and L.M. Mohaidat, 2010. Multilevel linear models analysis using generalized maximum entropy. Asian J. Math. Stat., 3: 111-118.
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  35. Eidous, O., 2009. Kernel method starting with half-normal detection function for line transect density estimation. Commun. Stat.-Theory Methods, 38: 2366-2378.
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  36. Ebrahem, M.A.H., O. Eidous and G. Kmail, 2009. Estimating percentiles of time-to-failure distribution obtained from a linear degradation model using kernel density method. Commun. Stat.-Simul. Comput., 38: 1811-1822.
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  37. Baklizi, A. and O. Eidous, 2009. Testing exponentiality using kernel-based entropy estimates. Bull. Stat. Econ., 3: 76-83.

  38. Baklizi, A. and O. Eidous, 2008. Goodness of fit tests for normality based on kernel entropy estimators. Bull. Stat. Econ., 2: 19-25.

  39. Eidous, O.M. and A.Q. Al-Masri, 2006. Kernel-exponential model for line transect density estimation. Pak. J. Stat., 22: 51-61.

  40. Eidous, O., 2006. A semiparametric model for line transect sampling. Commun. Stat.-Theory Methods, 35: 1211-1221.
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  41. Baklizi, A. and O. Eidous, 2006. Nonparametric estimation of P(X< Y) using kernel methods. Metron, 64: 47-60.

  42. Eidous, O.M., 2005. On improving kernel estimators using line transect sampling. Commun. Stat.-Theory Methods, 34: 931-941.
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  43. Eidous, O.M., 2005. Histogram and polygon methods using line transect sampling. J. Applied Stat. Sci., 14: 25-36.

  44. Eidous, O.M., 2005. Bias correction for histogram estimator using line transect sampling. Environmetrics, 16: 61-69.
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  45. Eidous, O., 2005. Frequency histogram model for line transect data with and without the shoulder condition. J. Korean Stat. Soc., 34: 49-60.

  46. Eidous, O., 2004. Some improvements in kernel estimation using line transect sampling. J. Modern Applied Stat. Methods, 3: 149-157.

  47. Eidous, O., 2004. Some improvements for histogram estimator using line transect sampling. Pak. J. Stat., 20: 345-354.

  48. Eidous, O., 2004. A parametric family for density estimation in line transect sampling. Abhath Al-Yarmouk, 13: 315-326.

  49. Eidous, O. and A. Baklizi, 2004. Kernel-based estimation of P(X< Y) with paired data. J. Modern Applied Stat. Methods, 3: 143-148.

  50. Eidous, O., 2003. A combination model for line transect density estimation. Far East J. Theor Stat., 11: 31-42.
Member since November, 2017