Circular data (circular sightings) are periodic data and are measured on the unit's circle by radian or grades. They are fundamentally different from those linear data compatible with the mathematical representation of the usual linear regression model due to their cyclical nature. Circular data originate in a wide variety of fields of scientific, medical, economic and social life. One of the most important statistical methods that represents this data, and there are several methods of estimating angular regression, including teachers and non-educationalists, so the letter included the use of three models of angular regression, two of which are teaching models and one of which is a model of educators. ) (DM) (MLE) and circular shrinkage model (Circular Shrinkage Method) (SH) This method is a method proposed by the researcher, and the non-educational model is the circular positional regression model Local Linear Circular Regression (LL), and the Mean Circular Error (MCE) criterion was used to compare the three models. The results were shown on the experimental side (simulation) using inverse method (inverse method) and using R language software, in simulation experiments (9 experiments) and for all default values, Lack of preference for teacher models compared to non-teacher models.
Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro
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أن الطرق اللامعلمية هي نوع من الطرق الاحصائية الاستدلالية التي يمكن استخدامها للتوصل إلى أستنتاجات لذا كان حرص المؤلف على أصدار هذا الكتاب والذي يعمل على توضيح ( لماذا ؟ ومتى ؟ وكيف ؟ ) تستخدم كل طريقة إحصائية . وبإمكان القاريء سواء أكان أستاذا ً جامعيا ً أو باحثا ً أو طالبا ً في الدراسات العليا ( الماجستير والدكتوراه ) أو طالبا ً في الدراسات الأولية أن يتتبع جميع الخطوات لحساب كل قانون إحصائي وبدءا ً من عملية إدخ
... Show MoreArtificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreGeneralized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
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The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.
Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the
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Many researchers have tackled the shear behavior of Reinforced Concrete (RC) beams by using different kinds of strengthening in the shear regions and steel fibers. In the current paper, the effect of multiple parameters, such as using one percentage of Steel Fibers (SF) with and without stirrups, without stirrups and steel fibers, on the shear behavior of RC beams, has been studied and compared by using Finite Element analysis (FE). Three-dimensional (3D) models of (RC) beams are developed and analyzed using ABAQUS commercial software. The models were validated by comparing their results with the experimental test. The total number of beams that were modeled for validation purposes was four. Extensive pa
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This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.
The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.
After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re
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