In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and the hazard function are found. The behaviour of probability density function for MWPDTI distribution by representing the values of This means, the probability density function of this distribution treats the period (0,1] which is ignore in SPDTI.
Gypsum is one of the important construction materials in Iraq in plastering surfaces and gypsum board , the ability of gypsum to give a comfortable an aesthetic ambiance as a construction material increase the need of gypsum , The particle size , total surface area and particle size distribution were factors affecting plaster properties used for construction properties . In this study gypsum paste was used with different mixing ratios of particle size and studied the physical properties of these types of pastes named (standard consistency ,setting time ,density) and compressive strength . The results showed that the water to gypsum ratio increased with increasing the fineness of the gypsum to (0.75%) and the setting time to the maxi
... Show MoreIn this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.
Additionally Maximum likelihood estimation method
... Show Moreان الهدف من البحث هو تقويم منهاج الفيزياء للصف الاول الثانوي في الجمهورية اليمنية
New class A^* (a,c,k,β,α,γ,μ) is introduced of meromorphic univalent functions with positive coefficient f(z)=□(1/z)+∑_(n=1)^∞▒〖a_n z^n 〗,(a_n≥0,z∈U^*,∀ n∈ N={1,2,3,…}) defined by the integral operator in the punctured unit disc U^*={z∈C∶0<|z|<1}, satisfying |(z^2 (I^k (L^* (a,c)f(z)))^''+2z(I^k (L^* (a,c)f(z)))^')/(βz(I^k (L^* (a,c)f(z)))^''-α(1+γ)z(I^k (L^* (a,c)f(z)))^' )|<μ,(0<μ≤1,0≤α,γ<1,0<β≤1/2 ,k=1,2,3,… ) . Several properties were studied like coefficient estimates, convex set and weighted mean.
In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as the Bayes method. The comparison was made using the mean error squares (MSE), where the best estimator is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).
A fast moving infrared excess source (G2) which is widely interpreted as a core-less gas and dust cloud approaches Sagittarius A* (Sgr A*) on a presumably elliptical orbit. VLT
In individuals with type 2 diabetes mellitus (T2DM), the cannabinoid receptor 1 (CNR1) gene polymorphism has been linked to diabetic nephropathy (DN). Different renal disorders, including DN, have been found to alter cannabinoid (CB) receptor expression and activation. This cross-sectional study aimed to investigate the relationship between CNR1 rs1776966256 and rs1243008337 genetic variants and the risk of developing DN in Iraqi patients with T2DM. The study included 100 patients with T2DM, divided into two groups: 50 with DN and 50 without DN. Genotyping of CNR1 rs1776966256 and rs1243008337 polymorphisms was conducted using PCR in DN patients and control samples. The distribution of rs1776966256 and rs1243008337 genotypes and alleles bet
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