Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime. The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method. Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq. Oil prices directly affect the health of the economy. Thus, it is necessary to forecast future oil price with models adapted for emerging events. In this article, we st

In this research work an attempt has been made to investigate about the Robustness of the Bayesian Information criterion to estimate the order of the autoregressive process when the error of this model,  Submits to a specific distributions and different cases of the time series on various size of samples by using the simulation,  This criterion has been studied by depending on ten distributions, they are (Normal, log-Normal, continues uniform, Gamma , Exponential, Gamble, Cauchy, Poisson, Binomial, Discrete uniform) distributions, and then it has been reached to many collection and recommendations related to this object , when the series residual variable is subject to each  ( Poisson , Binomial , Exponential , Dis

The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

We demonstrate that the selective hydrogenation of acetylene depends on energy profile of the partial and full hydrogenation routes and the thermodynamic stability of adsorbed C₂H₂ in comparison to C₂H₄.

The performance of H2S sensor based on poly methyl methacrylate (PMMA)-CdS nanocomposite fabricated by spray pyrolysis technique has been reported. XRD pattern diffraction peaks of nano CdS has been indexed to the hexagonally wurtzite structured The nanocomposite exhibits semiconducting behavior with optical energy gap of4.06eV.SEM morphology appears almost tubes like with CdS/PMMA network. That means the addition of CdS to polymer increases the roughness in the film and provides high surface to volume ratio, which helps gas molecule to adsorb on these tubes. The resistance of PMMA-CdS nanocomposite showed a considerable change when exposed to H2S gas. Fast response time to detect H2S gas was achieved by using PMMA-CdS thin film sensor. The

Photodetector based on Rutile and Anatase TiO₂ nanostructures/n-Si Heterojunction