This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

Physical and chemical adsorption analyses were carried out by nitrogen gas using ASTM apparatus at 77 K and hydrogen gas using volumetric apparatus at room temperature respectively. These analyses were used for determination the effect of coke deposition and poisoning metal on surface area, pore size distribution and metal surface area of fresh and spent hydrodesulphurization catalyst Co-MoAl2O3 .Samples of catalyst (fresh and spent) used in this study are taken from AL-Dura refinery. The results of physical adsorption shows that surface area of spent catalyst reduced to third compare with fresh catalyst and these catalysts exhibit behavior of type four according to BET classification ,so, the pores of these samples are cylindrical, and the

      In this work, a new formula of intensity distribution in image plane of elliptical object was founded (Elliptical spread function), by using optical system including circular aperture. The Gauss quadrature method of numerical integral was used for calculating equation's integrals. Curves are shown for system having focal error and intensity distribution in focal axis.  

 Alternative  distribution  to estimate the Dose – Response  model in bioassay  excrement

This research   concern to study five different distribution (Probit , Logistic, Arc sine , extreme value , One hit  ), to estimate  dose –response model by using m.l.e  and probit method This is done by determining different  weights in each  distribution in addition find all particular statistics for vital model . 

16S rRNA gene sequence examination is an effective instrument for characterization of new pathogens in clinical specimens. Akey component of colonization, biofilm formation, and protection of the pragmatic human pathogen Pseudomonasaeruginosais the biosynthesis of the exopolysaccharide Psl.Extracellular polysaccharides,biofilm, are secreted by microorganisms into the neighboring environment and are significant for surface attachment and keeping structural safety within biofilms.Biofilm production is an important technique for the survival of P. aeruginosa,and its association with antimicrobial resistance represents a defy for patient therapeutics. The aim of the current research is to assess the antibiotic resistance manner and distribution

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio

A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re