A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjusted) values.
Seemingly Unrelated Regression Model to Measure the Profitability of Some Iraqi Private Commercial Banks with Presence of Outliers
Seemingly uncorrelated regression (SUR)
Outliers
Contemporaneous Correlation
GLS Estimation Method
Robust SUR Estimators
FastSUR Estimator.
Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
COVID-19
Chest X-ray
Li s' method
Particle swarm intelligence
Laws' masks
Gray level co-occurrence matrix (GLCM)
Weighted voting
Support vector machine (SVM)
(22)
(5)
Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة مقدرات بيز لدالة المعولية لتوزيع باريتو من النوع الاول باستعمال دوال معلوماتية مضاعفة مختلفة
Pareto type I distribution
reliability function
bayes method
double prior distributions (chi-gamma square distribution. gamma- erlang distribution
erlang exponential distribution
the squared error loss function.
توزيع باريتو من النوع الاول
دالة المعولية
طريقة بيز
الدوال المعلوماتية المضاعفة : توزيع مربع كاي- كاما
توزيع كاما - ارلنك
التوزيع ارلنك- الاسي
دالة الخسارة التربيعية.
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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