A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

Background: with the advent of new postmaterial in dentistry, it has become important to measure fitness of post restoration along the horizontal plane of the root space.This study aimed to measure and compare, the cement film thickness of conventional zinc phosphate cement in micrometer between the post and root dentin along horizontal plane at different post space regions (coronal, middle and apical) of four types of posts, by using stereomicroscopy. Material and methods: Thirty-two extracted human maxillary canines, mandibular canines and maxillary central incisors (n=32) were instrumented with ProTaper system files (hand use) and obturated with gutta-percha for ProTaper and AH26® root canal sealer. After 24hrs of incubation at 37ºC, p

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

     The control charts are one of the scientific technical statistics tools that will be used to control of production and always contained from three lines  central line and upper, lower lines to control quality of production and represents set of numbers so finally the operating productivity under control or nor than depending on the actual observations. Some times to calculating the control charts are not accurate and not confirming, therefore the Fuzzy Control Charts are using instead of Process Control Charts so this method is more sensitive, accurate and economically for assisting decision maker to control the operation system as early time. In this project will be used set data fr

Background: The apical seal is the single most important factor in determining the success of surgical endodontics, the aim of this study was to compare the sealing ability of Mineral Trioxide Aggregate in three different cavity designs. Materials and Methods: Thirty extracted human single-rooted teeth were divided into three groups of ten teeth per group, a retrograde cavity preparation was carried out using a low speed handpiece and round bur with parallel walls in the first group, ultrasonic retrotip and unit in the second group and a low speed handpiece with a carbide inverted cone bur with undercuts in the third group, all the cavities were filled with MTA. microleakage was measured by dye penetration technique using methylene blue. Re

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