000 02855cam a2200337 a 4500
003 EG-GiCUC
005 20250223031710.0
008 170328s2016 ua f m 000 0 eng d
040 _aEG-GiCUC
_beng
_cEG-GiCUC
041 0 _aeng
049 _aDeposite
097 _aPh.D
099 _aCai01.18.03.Ph.D.2016.Ah.N
100 0 _aAhmed Ramzy Mahmoud Shehata
245 1 0 _aNew goodness of fit tests under censoring schemes /
_cAhmed Ramzy Mahmoud Shehata ; Supervised Samir Kamel Ashour , Waleed Mohamed Afify
246 1 5 _aاختبارات جديدة لجوده التوفيق تحت خطط مراقبه
260 _aCairo :
_bAhmed Ramzy Mahmoud Shehata ,
_c2016
300 _a216 Leaves ;
_c30cm
502 _aThesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics
520 _aAt the core of all statistical analyses, there exists a model that attempts to describe the underlying structure or relationship of some phenomena on which measurements are taken. Statistical tests, estimation procedures, and inference are based on these sampled measurements data) and a hypothesized model. Procedures used to verify and validate these model or distributional assumptions are known as goodness of fit tests. One popular approach for testing a goodness of fit is based on a discrepancy measure between the empirical distribution function and the hypothesized distribution function. Examples include the well known goodness of fit tests of a fully specified null hypothetical distribution to data are the kolmogorov smirnov (KS), cramer von mises (CvM) and anderson darling (AD) tests. recently, grane' (2012) proposed another approach for testing a completely specified goodness of fit test with type-II censoring schemes that based on hoeffding's maximum correlation. Also goldmann et al. (2015) suggested approach to test a goodness of fit with type-II censoring samples based on data transformations. In this study, we restrict our attention to modify these tests for flexible weibull and inverse flexible Weibull distributions. The maximum likelihood method of estimation is used for estimating the parameters. Critical values are obtained for the modified KS, CvM and AD test statistics in case of complete and type-II censored samples, a goodness of fit test based on data transformations and a goodness of fit test based on Hoeffding's maximum correlation with type-II censoring schemes through monte Carlo simulation
530 _aIssued also as CD
653 4 _aCensoring schemes
653 4 _aFit tests
653 4 _aNew goodness
700 0 _aSamir Kamel Ashour ,
_eSupervisor
700 0 _aWaleed Mohamed Afify ,
_eSupervisor
856 _uhttp://172.23.153.220/th.pdf
905 _aNazla
_eRevisor
905 _aSamia
_eCataloger
942 _2ddc
_cTH
999 _c60459
_d60459