AbstractBackgroundLeishmaniasis is endemic in Iraq, where both cutaneous and visceral forms of the disease are reported.ObjectivesTo determine the prevalence of cutaneous leishmaniasis (CL) and to identify associations of CL with age, sex, season, and provinces depending on some demographic and climatic aspects.MethodsThis study is retrospective and includes reported cases of infections using the available surveillance database taken from the Iraqi Ministry of Health for the years 2011, 2012, and 2013 for all provinces of Iraq.ResultsMen and boys were found to be at higher risk for CL compared with women and girls. The majority of cases were recorded among those in age groups 5–14 and 15–45 years old. Most cases were recorded from lowla

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

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.