TY  - BOOK
AU  - Mohamed Ali Ahmed Mahmoud 
AU  - Elsayed Ahmed Elsherpieny , 
AU  - Mahmoud Riad Mahmoud , 
TI  - Extending Kumaraswamy family of generalized distributions / 
PY  - 2016///
CY  - Cairo : 
PB  - Mohamed Ali Ahmed Mahmoud , 
KW  - Kumaraswamy generalized distributions
KW  - Moment  generating function
KW  - Quantiles
N1  - Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics; Issued also as CD
N2  - Finding the best fitted distribution for data set becomes practically  an important problem in world of data sets so that it is useful to use  new families of distributions to fit more cases or get better fits than  before. In this thesis, a new generating family of generalized  distributions so called the Kumaraswamy - Kumaraswamy (Kw Kw)  family is presented. Four important common families of distributions are  illustrated as special cases from the Kw Kw family. Moments,  probability weighted moments, moment generating function, quantile  function, median, mean deviation, order statistics and moments of  order statistics are obtained. Parameters estimation and variance  covariance matrix are obtained using maximum likelihood method.  The Kumaraswamy - Kumaraswamy Weibull (Kw Kw Wi)  distribution is derived, as a special case from the Kw Kw familly, and we  show that it generalizes many important distribution. The pdf, the cdf,  moments, quantile, the median, the mode, the mean deviation, the  entropy, order statistics, L-moments, extreme value and unknown  parameters estimation based on maximum likelihood are obtained for  the Kw Kw Wi distribution. A simulation study and a real data set are used to illustrate the potentiality and applications of the new Kw Kw Wi  distribution
UR  - http://172.23.153.220/th.pdf
ER  -