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

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

The optimum conditions for production of fibrinolytic protease from an edible mushroom Pleurotus ostreatus grown on the solid medium , Sus medium, composed of Sus wastes (produced from extracted medicinal plant Glycyrrhiza glabra) were determined. Addition of 5% of Soya bean seeds meal in Sus medium recorded a maximum fibrinolytic protease activity resulting in 7.7 units / ml. The optimum moisture content of Sus medium supplemented with 5% Soya bean seeds meal was 60% resulting in 7.2 units / ml.Pleurotus ostreatus produced a maximum fibrinolytic protease activity when the spawn rate,pH of medium and incubation temperature were 2,6 and 30°C, respectively. The maximum fibrinolytic protease activity was 7.6 units / ml when incubat

    The aqueous and methanol extracts of Salvia officinals and Salix acmoplylla traditionally used for the treatment of infections disease were tested for their active  against gram positive and gram negative bacteria isolated from wound  infection culture using the broth dilution and disc diffusion melhod. Results of   this study revealed the prescence of phytochemical which were  active  against gram positive and negative bacteria. Methanol extracts of both plants showed  the highest activity other the aqueous extract. The minimum inhibitory concentration (MIC) of the aqueous extracts on the test organism was  25- 100 mg\ml,while that of the  methanol extract was ranged betwee

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

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 distrib

In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.