In this research estimated the parameters of Gumbel distribution Type 1 for Maximum values through the use of two estimation methods:- Moments (MoM) and Modification Moments(MM) Method. the Simulation used for comparison between each of the estimation methods to reach the best method to estimate the parameters where the simulation was to generate random data follow Gumbel distributiondepending on three models of the real values of the parameters for different sample sizes with samples of replicate (R=500).The results of the assessment were put in tables prepared for the purpose of comparison, which made depending on the mean squares error (MSE).
This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The
... Show MoreWater is necessary for sustainable development and healthy society. Groundwater, often, is not sufficient and protected for direct human consumption. Due to increase in the density of population the requirement of water is increasing. In this work, the assessment of groundwater quality was conducted in the south-west part of Basrah province. Spatial variations in the quality of groundwater in the study area have been analyzed utilizing GIS technique. The geochemical parameters of groundwater samples including pH, EC, TDS, Ca, Mg, Na, Cl, HCO3, SO4, and NO3 were assessed in this study. Information maps of the study area have been actually prepared to make use of the GIS spatial
... Show MoreIn this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes
In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using the simulation.
This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulat
... Show MoreThe present work concerns with simulating unsteady state equilibrium model for production of methyl oleate (biodiesel) from reaction of oleic acid with methanol using sulfuric acid as a catalyst in batch reactive distillation. MESHR equations of equilibrium model were solved using MATLAB (R2010a). The validity of simulation model was tested by comparing the simulation results with a data available in literature. UNIQUAC liquid phase activity coefficient model is the most appropriate model to describe the non-ideality of OLAC-MEOH-MEOL-H2O system. The chemical reactions rates results from EQ model indicating the rates are controlled by chemical kinetics. Several variables was studied such as molar ratio of methanol to oleic acid 4:1, 6:1
... Show MoreThis paper is devoted to compare the performance of non-Bayesian estimators represented by the Maximum likelihood estimator of the scale parameter and reliability function of inverse Rayleigh distribution with Bayesian estimators obtained under two types of loss function specifically; the linear, exponential (LINEX) loss function and Entropy loss function, taking into consideration the informative and non-informative priors. The performance of such estimators assessed on the basis of mean square error (MSE) criterion. The Monte Carlo simulation experiments are conducted in order to obtain the required results.
Abstract
At any moment, the continuous usage of medications can accompanied by DNA damage and the accumulation of such damages can cause serious consequences. Antidepressants are long-term used drugs and the incidence of their genotoxic impacts cannot be excluded. Therefore, this work was designed to investigate the possible genotoxic effects of the commonly used antidepressants (fluoxetine and amitriptyline) in adult male rats.
Detection of DNA damage in individual cells was assessed by comet and micronucleus assays in three different cell populations i.e. liver, testis and bone marrow tissues of 24 swiss albino adult male rats. The animals were randomly allocated into three groups of 8 rats ea
... Show MoreHR Ghanim, GA Abdulhassan, International Journal of Early Childhood Special Education, 2022
Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem
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