On the generation of new generalized families of distributions with applications

In this thesis, new generalized families of distributions namely, Weibull Odd

Burr III-G (WOBIII-G), Ristic-Balakhrishnan Odd Burr III-G (RBOBIII-G), Risti ´ c-´

Balakhrishnan Marshall-Olkin-G (RBMO-G), Exponentiated Half-Logistc Odd Burr

III-G (EHL-OBIII-G) and Half-Logistic Odd Power Generalized Weibull-G (HLOPGW G) families of distributions are developed and studied in detail. Furthermore, the

mathematical and statistical properties of these new families of distributions such

as moments and moment generating functions, order statistics, probability weighted

moments, stochastic ordering and Renyi entropy are derived and studied in detail. ´

We use some of the existing known baseline models to generate some special cases

for these newly generated families of distributions. The maximum likelihood estimation technique is used to estimate model parameters and simulation experiments

are conducted to illustrate the consistency of maximum likelihood estimates. Finally

we demonstrate the efficacy and flexibility for some of the special cases under these

distributions by fitting them to some real data sets. The proposed models presents

better fits than other existing equal parameter models.