An evaluation of pollution level has been done for drinking water which is used in Kirkuk city by heavy metals ( As,Cd,Cu,Fe,Mn,Ni,Zn,Cr,Pb) samples were collected during wet and dry of 2016-2017 from Kirkuk unified water supplied project (WTP) which is supply the city with drinking water, as well as from water of tanks type (GST2), and also from (tap water) (Zone3). The results showed the concentration of the (As,Cd,Cu,Fe,Mn,Ni,Zn,Cr,Pb)inppbfor (WTP)are (0.5,0.6,6.45,38,4.6,2.5,6537,0.58,1.4) (0.6,0.8,6.76,46,5.5,3.5,6675,1,2.4) for (GST) (0.5,0.63,6.46,52.3,4.4,3.6,6550,0.6,2.5) (0.60,0.7,6.78,63.7,6.7,3.7,6680,1.1,2.6) and for tap water are (0.53,0.65,7.00,60.2,4.4,3.65,7200,0.8,2.7) (0.60, 0.71, 7.10, 67.6, 6.8,3.75,7320,0.9,2.75) f

The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

     In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates  sample size , and it replicates  for the real value for parameters, for reliability times values  we take .

Results were compared by using mean square error (MSE), the result appears as follows :

The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation technique .. It was obse

      The present paper concern with minimax shrinkage estimator technique in order to estimate Burr X distribution shape parameter, when prior information about the real shape obtainable as original estimate while known scale parameter.

 Derivation for Bias Ratio, Mean squared error and the Relative Efficiency equations.

 Numerical results and conclusions for the expressions mentioned above were displayed. Comparisons for proposed estimator with most recent works were made.

This paper deals with constructing mixed probability distribution from mixing exponential

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

In this research estimated the parameters of Gumbel distribution Type 1 for Maximum values through the use of two estimation methods:- Moments (MoM) and Modification Moments(MM) Method. the Simulation used for comparison between each of the estimation methods to reach the best method to estimate the parameters where the simulation was to generate random data follow Gumbel distributiondepending on three models of the real values of the parameters for different sample sizes with samples of replicate (R=500).The results of the assessment were put in tables prepared for the purpose of comparison, which made depending on the mean squares error (MSE).