The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
Abstract
This research attempt to explain the essential aspects of one important model in management of Bank risks , that is (stress testing) , which increase the concentrate on it resulting the negative affects of Global financial crisis that it accuar in 2008 to study the application possibilities in iraqian banks to enhancing the safety and financial soundness Becuase the classical tools in Risk management don’t give clear image on Banks ability in facing risks, hence the Basel committee on Banking supervision focusing in agreement of Basel 2,3 on stress testing when it doing the internal capital adequacy assessment process (ICAAP) .
To achieving the reseach obje
... Show MoreIn this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number determines the persistence or extinction of the COVID-19. If , one infected cell will transmit the virus to less than one cell, as a result, the person carrying the Coronavirus will get rid of the disease .If the infected cell will be able to infect all cells that contain ACE receptors. The stochastic model proves that if are sufficiently large then maybe give us ultimate disease extinction although , and this facts also proved by computer simulation.
This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others
In this paper, the effect of changes in bank deposits on the money supply in Iraq was studied by estimating the error correction model (ECM) for monthly time series data for the period (2010-2015) . The Philips Perron was used to test the stationarity and also we used Engle and Granger to test the cointegration . we used cubic spline and local polynomial estimator to estimate regression function .The result show that local polynomial was better than cubic spline with the first level of cointegration.
A streptococci has recognized as Streptococcus spp., associate with acute pharyngitis. S. pyogenes infection Has detected in the Hospital and Health Center in Tikrit city. Throat swabs sample has obtained and cultured on a sheep blood agar plate. Identification of S. pyogenes was performed by using the VITEK 2 automatic system. It detected of 50 samples from children included 25 were positive for S. pyogenes infection. were aged 10-35 years old and included 30 male and 20 female. . While 25 sample Negative of S. pyogenes infection (The control group included 25 clinically healthy children without S. pyogenes infection matched for age and sex with cases pateints). No significa
... Show MoreIn this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.
Abstract
Oil is considered a commodity and is still an important and prominent role in drawing and shaping the Iraqi economic scene. The revenues generated from the export of oil are considered the main source of the general budget in cash flows.
Since the revenues consist of quantity and price and the latter is an external factor which is difficult to predict, The effect of any commodity on its price, which is proven in the theory of micro-economic, but it is observed through the research that the response is slow, which means not to take advantage of the rise in prices, by increasing the quantity exported, the result of several facto
... Show MoreIn this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.
The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
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