Pareto distribution is used in many economic, financial and social applications. This distribution is used for the study of income and wealth and the study of settlement in cities and villages and the study of the sizes of oil wells as well as in the field of communication through the speed of downloading files from the Internet according to their sizes. This distribution is used in mechanical engineering as one of the distributions of models of failure, stress and durability. Given the practical importance of this distribution on the one hand, and the scarcity of sources and statistical research that deal with it, this research touched on some statistical characteristics such as derivation of its mathematical function , probability density function, cumulative distribution function, methods of estimating parameters, and the difficulties that researchers may face in dealing with these phenomena. The parameters were estimated in a number of methods, including the Maximum Likelihood (MLE), Ordinary Least Squares (OLS), Moment method (MOM), Relative Least squares (RELS) and Ridge regression (RR). In addition an algorithm has been proposed to improve the estimation parameters for this distribution. MSE was used to determine the best of these methods. Conclusions were presented in the light of this and appropriate proposals were decided upon.
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Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.
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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
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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
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Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu
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Objectives:This study aimed to identify women perception and experience regarding family planning(FP) methods
Methodology:Descriptive cross-sectional hospital based study,was conducted at Omer Sawi teaching hospital,from august to September 2019.Sample of 320 women, were selected randomly after their agreement.Data were collected through interview questionnaire and analyzed using a statistical package for social sciences (SPSS)and descriptive and inferential statistical methods were used.With accepted P.< 0.05.for the correlation significant.
Results:Age group between 21-25 years represent (53.1%),most common education levels were secondary school 56%.Majority of women had 2-5 children.Half of the wo
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Objectives: to assess chronic diseases patients’ knowledge toward stroke risk factors and warning signs, besides
determining the relationship between chronic diseases patients’ knowledge and their sociodemographical
characteristics.
Methodology: A descriptive study was carried out at public medical clinics which has started from December
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nd, 2008 to August 8th, 2009. A purposive "non-probability" sample of (300) chronic diseases individuals who
were clients of Public Medical Clinics who have one or more of the following chronic diseases (hypertension,
diabetes mellitus, heart diseases, and previous stroke), in Baghdad city. The data were collected through the use
of a constructed questionnaire which consists
Objective: To determine the effectiveness of an Educational Program in Enhancing Nurse’s Knowledge about Occupational Health Hazards at Medical City Hospitals in Baghdad City.
Methodology: The present study employed a quasi-experimental design held at Medical City Hospitals in Baghdad City. A non-probability sample (convenience sample) consisted of (60) nurse. Data were collected by using a self-report questionnaire which consisted of six parts (a) socio-demographic characteristics (b) physical hazards knowledge (c) chemical hazards knowledge (d) biological hazards knowledge (e) psychological hazards knowledge and (f) mechanical hazards knowledge. Data were analyzed using the statistical packag
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