@inproceedings{scholars17229, pages = {326--332}, title = {A New Odd F-Weibull Distribution: Properties and Application of the Monthly Nigerian Naira to British Pound Exchange Rate Data}, journal = {2022 International Conference on Data Analytics for Business and Industry, ICDABI 2022}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, doi = {10.1109/ICDABI56818.2022.10041527}, year = {2022}, note = {cited By 3; Conference of 2022 International Conference on Data Analytics for Business and Industry, ICDABI 2022 ; Conference Date: 25 October 2022 Through 26 October 2022; Conference Code:186761}, author = {Ishaq, A. I. and Usman, A. and Tasi'u, M. and Suleiman, A. A. and Ahmad, A. G.}, isbn = {9781665490580}, keywords = {Failure rate; Finance; Maximum likelihood, Distribution applications; Exchange rates; Failure rate; Generating functions; Information generating function; Nigerians; Odd F generalized family; Odd F-weibull; Quantile functions; Weibull, Weibull distribution}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149266306&doi=10.1109\%2fICDABI56818.2022.10041527&partnerID=40&md5=eb26c11490d4e2af80d94f6cf984bd61}, abstract = {This study developed a novel generalized family of probability distributions known as the Odd F generalized family of distribution. The compound Odd F-Weibull distribution was introduced from the Odd F generalized family. This distribution is an alternative to various current distributions, such as the Beta-Weibull distribution, Generalized Modified Weibull, Log-Logistic-Weibull, Frechet-Weibull and Exponentiated Exponential-Weibull distributions. We obtained the distributions of quantile function, moments and information-generating function. Moreover, the parameters of its estimates were derived using the maximum likelihood approach. Furthermore, monthly Nigerian Naira to British Pound exchange rate data was analyzed to verify the viability of developed model. The findings demon-strate that the Odd F-Weibull model outperformed better than competitive distributions by having minimal corrected akaike information and Bayesian information criteria values. {\^A}{\copyright} 2022 IEEE.} }