The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the meth

In this paper ,the problem of point estimation for the two parameters of logistic distribution has been investigated using simulation technique. The rank sampling set estimator method which is one of the Non_Baysian procedure and Lindley approximation estimator method which is one of the Baysian method were used to estimate the parameters of logistic distribution. Comparing between these two mentioned methods by employing mean square error measure and mean absolute percentage error measure .At last simulation technique used to generate many number of samples sizes to compare between these methods.

Shatt al-Arab is the only navigational artery in Iraq, extending from the city of Qurna to its mouth in the Arabian Gulf at the city of Al-Fao within the governorate of Basrah for a length of approximately 204 km. Its width ranges from 400 m to 2000 m, and its depth ranges from 8 m to 20 m. The southern part of it, 93 km long from Umm al-Rassas Island to Ras al-Bisha, represents the international border between Iraq and Iran, where the Thalweg line represents the border between the two countries, which is the deepest point in the riverbed (according to the 1975 Algiers Agreement). The western bank (the Iraqi side) within the common border of Shatt al-Arab is subject to continuous erosion, which leads to the shifting of t

The aim of this research is to determine the uranium concentration in soil and water samples taken from different locations from the middle and south of Iraq using fission fragments track registration. Twelve samples of soil and water were taken from middle and South of Iraq. The nuclear reaction used as a source of nuclear fission fragments is U-235 (n.f) obtained by bombardment U-235with thermal neutrons from (Am-Be) neutron source with flux (5X103 n.cm-2.s-1). The concentration values were calculated by a comparison with standard samples recommended by IAEA.The results of the measurements show that the uranium concentration in soil samples were in Thekar (16.38 ppm), AL-Basra (16.1ppm) and (0.78 ppm) in Baghdad, from the results

In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; w_i  where  0 < w_i < 1 ­and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter,  and the second also has the scale parameter , and the shape parameter,  in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion