The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which prove

In this article we  study a single stochastic process model for the evaluate the assets pricing and stock.,On of the models le'vy . depending on the so –called Brownian subordinate as it has been depending on the so-called Normal Inverse Gaussian (NIG). this article aims as the estimate that the parameters of his model using my way (MME,MLE) and then employ those  estimate of the parameters is the study of stock returns and evaluate asset pricing for both the united Bank and Bank of North which their data were taken from the Iraq stock Exchange.

which showed the results to a preference MLE on MME based on the standard of comparison the average square e

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

This study included 46 patients with liver hydatid cyst diagnosed clinically and surgically, control group consist of 22 were naïve from infection had been confirmed by specialist. The patients were divided according to the size of the cysts into more and less than 5 cm diameter size, were 33 and 13 respectively. Also it divided into primary and secondary hydatid cyst infection which were 30 and 16 respectively. The role of immunological response against hydatid cyst parasite, showed a significant increased in humoral immunoglobulins (IgG, IgA, IgM and IgE) which were significantly higher in the hydatid cyst infection than control. Also significant increased in immunoglobulins in secondary infection than primary infection, beside significa

Out of 1279 stool sample only 245 were found to be infected with E.histolytica with total percentage 19% . Diagnostic study for E.histolytica by using techlab Eliza test showed that the non-pathogen E.dispar was significantly higher (78.9%) than E.histolytica (22%).We test the effect of the attenuated E. histolytica by gamma Radiation on the mortality rate in laboratory animals infected with E. histolytica by using increasing doses of radation (5,10,15,20and 25) Rad., the results showed that the percentage of mortality decrease when increase the dose of attenuated E.histolytica cyst in comparison with positive control group (non – attenuated group) it reached (100% ,66.7%, 33.3% 0% and 0%)respectively. Also we found that gamma radiatio

To investigate the activity and role of certain enzyme markers in 30 patients female with breast cancer (non-treated, treated, and treatment with recovered).The serum activity of enzyme tumor markers (ALP, GPT and GOT) of (30) patients with breast cancer, and (7) healthy control subjects by using statistical analysis: There is significant difference higher in activity of serum enzyme tumor markers (ALP, GPT, and GOT) in all patients as compared with healthy control

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima