The monetary policy is a vital method used in implementing monetary stability through: the management of income and adjustment of the price (monetary targets) in order to promote stability and growth of real output (non-cash goals); the tool of interest rate and direct investment guides or movement towards the desired destination; and supervisory instruments of monetary policy in both quantitative and qualitative. The latter is very important as a standard compass to investigate the purposes of the movement monetary policy in the economy. The public and businesses were given monetary policy signals by those tools. In fiscal policy, there are specific techniques to follow to do the spending and collection of revenue. This is done in order to

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

Background: Ruptured uterus is a catastrophic event to both
mother and her fetus. Apart from maternal and fetal mortality
rates, the incidence of rupture of uterus is often taken as an
index of the standard of obstetric care.
Objective: To determine the frequency, causes, management
outcome of ruptured uterus at Al Batool maternity hospital.
Method: The study was conducted in the department of
obstetrics and gynecology at Al Batool maternity hospital
Mosul-Iraq over a period of three years from October 1st 2002
to August 30th 2005. All the cases of uterine rupture presented
during the study period were recorded and managed in the
department. Data was recorded on designed forms.
Results: Thirty nine cas

The research aims at determining the main reason for the deterioration of the services and determining the correct method of distributing the funds to the administrative and administrative units. The discrepancy between the size of the financial allocations and the municipal services was the main research problem. Therefore, the researcher identified the gaps in municipal services by the concerned departments and compared them with The percentage of funds obtained through the work of a checklist for each of the directorates concerned. The researcher studied the specific criteria for these services, which were approved by the Ministry of Construction, Housing, Municipalities, and Public Works, and compared them wi

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

This study deals with the Spatial and Periodical Variation of the Economical Activities for the
Population of Al – Anbar Province on the level of districts , according to the Population
Computation for the period 1987 and 1997 and the results of determinations and numberings
for the year of 2011 .
This study depends on the Details Classifications of the 17th Activities for 1997 and 2011
beside the Triple Classification of the Economical Activities for the three study years .
The study proves that there is a spatial and periodical variation on the level of study area , and
that’s because of many factors , one of the most important of them was the distribution of
economical siege, as well as the weakness of the