The aim of this paper is to estimate the concentrations of some heavy metals in Mohammed AL-Qassim Highway in Baghdad city for different distances by using the polynomial interpolation method for functions passing from the data, which is proposed by using the MATLAB software. The sample soil in this paper was taken from the surface layer (0-25 cm depth) at the two sides of the road with four distances (1.5, 10, 25 and 60 m) in each side of the road. Using this method, we can find the concentrations of heavy metals in the soil at any depth and time without using the laboratory, so this method reduces the time, effort and costs of conducting laboratory analyzes.
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I 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 Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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