dc.description.abstract | The concept of finite mixture has contributed immensely in search of more flexible distributions
that are in a position to capture data heterogeneity. One parameter Lindley
distribution as the first case of a finite mixed gamma distribution has been generalized
up to five parameters and goodness of fit measures done. Based on the available literature,
Lindley and its generalizations has been extensively applied in modeling of lifetime
data. Generalized cases of Lindley distribution prove to be more flexible than one parameter
Lindley in modeling lifetime data. However, Lindley and its generalizations have not
been extensively compared to other finite gamma mixtures. In this project, the goal is
to study finite gamma mixtures and their applications to lifetime data. Similarly, finite
gamma mixtures have been constructed up to three component and their statistical properties
studied.
Selected constructed finite gamma mixtureswere fitted to a lifetime data regarding carbon
fiber breaking stress recorded by Nichols and Padget (2006). The model parameters were
estimated using method of moments (MOM) and maximum likelihood (MLE) techniques.
The results of one parameter selected distributions proved that Suja, Rama, Aradhana, Sujatha,
Akash and Shanker were better fit than Lindley distribution. Based on the selected
distributions two parameter, it was established that QSD, AG2PAD, QAD, AG2PSD were
more flexible than AG2PLD while G2PSD performed worse than AG2PLD. Based on the
selected three parameter distributions fitted, AG3PLD was a better fit than AG3PAD and
AG3PSD. | en_US |