Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of cigarettes according to the US Federal Trade Commission.
In this paper has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi
... Show MoreThis study was aimed to isolate and identify Saccharomyces boulardii from Mangosteen fruits (Garcinia mangostana L.) by traditional and molecular identification methods To get safe and healthy foods probiotics for use, The isolates and two commercial strains were subjected to cultural, morphological and biochemical tests, The colonies of the isolates were spherical, smooth, mucoidal, dull and white to cream colour on SD agar media .The shape of cells was globose to ovoid and sometimes with budding, in a single form or clustered like a beehive. The isolates and two commercial strains were unable to metabolized galactose and lactose , Results shows that all isolates were unable to utilize potassium nitrate and not grow in the presence of (
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... Show MoreThis paper deals with estimation of the reliability system in the stress- strength model of the shape parameter for the power distribution. The proposed approach has been including different estimations methods such as Maximum likelihood method, Shrinkage estimation methods, least square method and Moment method. Comparisons process had been carried out between the various employed estimation methods with using the mean square error criteria via Matlab software package.
In this paper, analyzing the non-dimensional Magnesium-hydrodynamics problem Using nanoparticles in Jeffrey-Hamel flow (JHF) has been studied. The fundamental equations for this issue are reduced to a three-order ordinary differential equation. The current project investigated the effect of the angles between the plates, Reynolds number, nanoparticles volume fraction parameter, and magnetic number on the velocity distribution by using analytical technique known as a perturbation iteration scheme (PIS). The effect of these parameters is similar in the converging and diverging channels except magnetic number that it is different in the divergent channel. Furthermore, the resulting solutions with good convergence and high accuracy for the d
... Show MoreThe current study is the identification and isolation dermatophyte species in clinical isolates by both Sabouraud’s Dextrose Agar (SDA) and on Dermatophyte Test Medium (DTM). Clinical specimens of hair, nails and skin scales were collected from patients with dermatophytosis and submitted to direct microscopic examination after immersion in 20% of potassium hydroxide solution. The clinical specimens were cultured on SDA containing chloramphenicol and cycloheximide, and on DTM. Tinea corporis showed the highest prevalent dermatophyte infection among patients (26.7%), followed by Tinea pedis (23.3%), whereas Tinea manuum exhibited the lowest fungal infection (6.7 %). Rural areas revealed the highest prevalence of dermatophyte in
... Show MoreIn this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high
... Show MoreThe issue of liquidity, profitability, and money employment, and capital fullness is one of the most important issues that gained high consideration by other authors and researchers in their attempts to find out the real relationship and how can balance be achieved, which is the main goal of each deposits.
For the sake of comprising the study variables, the research has formed the problem of the study which refers to the bank capability to enlarge profits without dissipation in liquidity of the bank which will negatively reflect on the bank's fame as well as the customers' trust. For all these matters, the researcher has proposed a set of aims, the important of which is the estimation of the bank profitability; liquid
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo
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