000			03297cam a2200349 a 4500
003			EG-GiCUC
005			20250223032440.0
008			191117s2019 ua f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.18.04.M.Sc.2019.En.C
100	0		_aEngy Saeed Mohamed Ahmed
245	1	2	_aA comparison of performance of residual control charts for some parametric and nonparametric regression models / _cEngy Saeed Mohamed Ahmed ; Supervised Sayed Mesheal Elsayed , Salah Mahdy Mohamed , Shereen Hamdy Abdellatif
246	1	5	_aمقارنة أداء خرائط ضبط البواقى لبعض نماذج الانحدار المعلمية و اللامعلمية
260			_aCairo : _bEngy Saeed Mohamed Ahmed , _c2019
300			_a137 Leaves ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Statistics and Econometrics
520			_aThe most important use of a control chart is to improve the performance by identify assignable causes. If these causes can be eliminated from the process, variability will be reduced and the process will be improved, focused on the statistical technique using the regression analysis in constructing regression residual control chart. Regression analysis is one of the most commonly statistical techniques used for analyzing data, describing the relation between the response variable and the explanatory variables. Parametric regression is assume a pre-specified form of the regression function. One of the most common parametric estimation methods is maximum likelihood estimation that is used in analysis for fitting the models. On the other side, the nonparametric regression models do not assume a pre-specified form of the regression function, and one of the nonparametric estimation method which used in analysis is the spline smoothing. The design of control charts is performed through two phase{u2019}s analysis. In phase I analysis, the stable control chart for regression residual will be suggested for monitoring by using X-bar /S-charts. In phase II analysis, the monitoring done by using EWMA control charts. A simulation study has been conducted to compare between the performance of deviance residuals, and Pearson residuals in case of parametric regression estimation and nonparametric regression estimation through EWMA control charts. Applications have been done using R program version 3.5.2 for fitting a gamma model with two different link functions; identity link function and log link function and extracting two different types of residuals; deviance residuals and pearson residuals, then the average run length measure has been calculated to evaluate the performance of residual control charts
530			_aIssued also as CD
653		4	_aParametric and nonparametric regression models
653		4	_aPerformance
653		4	_aResidual control charts
700	0		_aSalah Mahdy Mohamed Mohamed , _eSupervisor
700	0		_aSayed Mesheal Elsayed Tag Eldin , _eSupervisor
700	0		_aShereen Hamdy Abdellatif , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c75253 _d75253