In this paper, suggested formula as well a conventional method for estimating the twoparameters (shape and scale) of the Generalized Rayleigh Distribution was proposed. For different sample sizes (small, medium, and large) and assumed several contrasts for the two parameters a percentile estimator was been used. Mean Square Error was implemented as an indicator of performance and comparisons of the performance have been carried out through data analysis and computer simulation between the suggested formulas versus the studied formula according to the applied indicator. It was observed from the results that the suggested method which was performed for the first time (as far as we know), had highly advantage than t

In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

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

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Films of pure Poly (methyl methacrylate) PMMA and Iron chromate doped PMMA have been prepared using casting method. Transmission and absorptance spectra have been recorded in the wavelength range (300-900) nm, in order to calculate, single oscillator energy, dispersion energy proposed by Wemple - DiDomenico model, average oscillator strength, average oscillator wavelength. The refractive index data at infinite wavelength which was found to obey single oscillator model which was found to increase from 2.27-2.56 as the doping percentage increase. The decreasing in the optical energy gap which was found according to Tauc model were (3.74-3.63) eV , is in good agreement with that obtained by wimple-DiDomenico model. The inverse behavior comp

Thin Lithium Fluoride films have been prepared by thermal evaporation technique on glass substrate under vacuum of about 10-5mbar. The thickness of the films was 4000±50Å. The effects of annealing temperatures on the optical properties and dispersion parameters have been studies. Transmittance spectra of the films indicate that the films have high transparency. The optical absorption studies reveal that the transition is direct with band gap value varied with the annealing temperatures. Also the refractive index dispersion curves obey to the single oscillator's model. The dispersion energy and single-oscillator energy varied with the annealing temperatures

Background: Periodontal diseases are one of the major dental pathologies that affect human populations worldwide at high prevalence rates The term periodontal disease usually refers only to plaque related inflammatory disease of the dental supporting tissues. Mouth rinses which act as an anti-plaque agents mostly used as adjuncts to oral hygiene. Aims of the study: To Estimate and compare the effects of Aloe vera relative to chlorhexidine on the clinical periodontal parameters (plaque index, gingival index, bleeding on probing). Material and method: A total of 44 subjects with plaque-induced gingivitis, baseline of data were collected for (PLI, GI, and BOP) and underwent oral hygiene instruction, scaling and polishing, then divided into:

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).