In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

Benign prostatic hyperplasia (BPH) is one of the most common disease and major cause of morbidity in elderly men which may lead to bladder outflow obstruction and lower urinary tract symptoms (LUTS). Although sex steroid hormones play fundamental roles in prostate growth, their clinical significance is not completely clear. In the present study we assessed whether serum hormones levels as markers of prostate disease. This study includes (40) patients with benign prostatic hypertrophy and (40) control group with age rang (41-79) and (42-71) years respectively. The following biochemical investigations have been studied: Testosterone, Estradiol (E2), and Prostatic Specific Antigen (PSA) levels using ELISA method which correlated with t

A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a

The current world is observing huge developments in presenting the opportunity for organizations and administrative units to use information and communication technology and their adoption by administrative work due to its importance in the achievement of work with higher efficiency, speed, and facility of communication with all individuals and companies using various means of communication Depending on the Internet networks. Therefore, the research dealt with the study of electronic systems designed and adopted in the creation or construction of a database for archiving data, which is the main method in organizations and administrative units in developed countries. Where this system works to convert documents, and manual processes and t

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