A comparison between Robust regression analysis methods Applied statistical study of the most important demographic factors on the total fertility rate in Yemen for the period (1990-2013).
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Abstract
the research aims to compare the estimators of robust regression methods (the robustM method - the robust MM method - the robustS method), the detection of the nature of the distribution of data, the discovery of abnormal and extreme data of the study variables, in addition to revealing the stability of time chains, and testing a relationship Joint integration by analyzing the relationship between the studied demographic variables represented in (infant mortality - the number of maternal deaths - raw death rate - the rate of widespread malnutrition - female death rate - child mortality rate under the age For every 1,000 neighborhood births) as independent variables, and the total fertility rate as a variable in the Republic of Yemen for the period (1990-2015).
The research concluded with many results, the most important of which is that the best way to estimate the features of the stoned slope is the m fort- as it achieved the best values of the comparison standards of (RMSE-Mae-MAPE Theil Coefficient), and tests of abnormal values represented in (H) HAT showed -Matrix- Covratio - DFFITS) The study data suffers from abnormal values, and the study showed that the studied demographic variables affect the total fertility rate by 84%, while 14% belong to other factors that are not included in the estimated form.
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a robust regression model, a robust regression method, outlier values, unit root test, Johansson test
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