Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Jinan A. Naser Al-obedy"'
Autor:
Jinan A. Naser Al-obedy
Publikováno v:
Ibn Al-Haitham Journal for Pure and Applied Sciences, Vol 37, Iss 3 (2024)
In this paper, we investigated the Bayesian estimation of the unknown parameter of the Inverse Rayleigh Distribution (IRD) under different priors, represented by the inverse gamma distribution, the inverse chi-squared distribution, and the standard L
Externí odkaz:
https://doaj.org/article/4538da0298a141f5a659841ebc3c867a
Autor:
Jinan A. Naser Al-obedy
Publikováno v:
Ibn Al-Haitham Journal for Pure and Applied Sciences, Vol 36, Iss 3 (2023)
We are used Bayes estimators for unknown scale parameter when shape Parameter is known of Erlang distribution. Assuming different informative priors for unknown scale parameter. We derived The posterior density with posterior mean and posterior varia
Externí odkaz:
https://doaj.org/article/ff7ec8dc777848e296d1696b2d6a5d2f
Autor:
Jinan A. Naser Al-obedy
Publikováno v:
Ibn Al-Haitham Journal for Pure and Applied Sciences, Vol 35, Iss 1, Pp 60-72 (2022)
In this paper, Bayes estimators of Poisson distribution have been derived by using two loss functions: the squared error loss function and the proposed exponential loss function in this study, based on different priors classified as the two different
Externí odkaz:
https://doaj.org/article/1c42d68a86864fae84fb1f49721c5288
Autor:
Jinan A. Naser Al-Obedy
Publikováno v:
Journal of Economics and Administrative Sciences. 28:88-104
In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::674ee88387e3d4d31a15291361bd614a
https://doi.org/10.33095/jeas.v28i132.2274
https://doi.org/10.33095/jeas.v28i132.2274
Autor:
Jinan Abbas Naser Al-obedy
Publikováno v:
Journal of Economics and Administrative Sciences. 27:229-252
The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c66dcd65a65573c832274530c693cf7c
https://doi.org/10.33095/jeas.v27i127.2146
https://doi.org/10.33095/jeas.v27i127.2146
Autor:
Jinan Abbas Naser Al-Obedy
Publikováno v:
Journal of Economics and Administrative Sciences. 25:199-225
In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Ch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed4620896dd64d57d5056a2e22f63d1d
https://doi.org/10.33095/jeas.v25i116.1795
https://doi.org/10.33095/jeas.v25i116.1795
Autor:
Jinan Abbas Naser Al-obedy
Publikováno v:
Ibn AL-Haitham Journal For Pure and Applied Sciences. 30:208-236
In this study, we derived the estimation for Reliability of the Exponential distribution based on the Bayesian approach. In the Bayesian approach, the parameter of the Exponential distribution is assumed to be random variable .We derived posterior di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35af168aa2b3e8c117ff1ff28bc0e60d
https://doi.org/10.30526/30.1.1072
https://doi.org/10.30526/30.1.1072
Autor:
Jinan Abbas Naser Al-obedy
Publikováno v:
Journal of Economics and Administrative Sciences. 23:1
المستخلص: في هذا البحث , استعملنا طرائق مختلفة لتقدير معلمة القياس للتوزيع الاسي كمقدر الإمكان الأعظم ومقدر العزوم ومقدر بيز في ستة أنواع
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dded4225dbc5f3e3393b0e7d44fcfa9d
https://doi.org/10.33095/jeas.v23i99.267
https://doi.org/10.33095/jeas.v23i99.267