Browsing by Author "Adejumo, Adebowale"
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Item Cubic Transmuted Lindley as a Better Distribution in the Family of Rayleigh Distributions("Tibiscus" University of Timişoara, România, 2020-06) Adefowope, Adesiyan; Omekam, Ifeyinwa; Adejumo, AdebowaleA new statistical model for non-normal data is proposed with some of its statistical properties as Cubic of the Transmuted Lindley distribution (CTLD), based on a new family of life time distribution. The new model contains some of lifetime distributions as special cases such as exponentiated Lindley, transmuted Lindley and Lindley distributions. These include the density and hazard rate functions with their behavior, moments, and moment generating function, skewness and kurtosis measures. Maximum likelihood estimation of the parameters and their estimated are derived. An application of the model to a real data set is presented and compared with the fit attained by other well-known existing distributions.Item Derivations for the Families of Generalized Distributions("Tibiscus" University of Timişoara, România, 2017-12) Omekam, Ifeyinwa; Adejumo, AdebowaleGeneralization of distributions is usually motivated by limitations in characteristics of existing distributions so as to introduce more flexibility and improve goodness of fit. This is done by parameter induction into an existing distribution and therefore remains an approach to generalizing distributions. In this article, families of generalized distributions are generated by sequential application of methods in permutations of five distinct parameter induction methods: Lehmann Alternative 1 (LA1); Lehmann Alternative 2 (LA2); Marshal and Olkin Method (M-OM); α-Power Transformation (APT); and Power Transformation Method (PTM). This is done by taken two methods at a time. Sixteen distinct families of generalized distributions were generated. Some of the families of generalized distributions obtained are already in existence while several others are entirely new.Item Flexibility of Generalized Distributions(Royal Statistical Society Nigeria Local Group, 2022-09-12) Omekam, Ifeyinwa; Adejumo, AdebowaleSome existing distributions are limited in shapes of Probability Density Function (PDF) and Hazard Function (HF) which constrains their use in analysis of certain types of data. Generalizing these distributions often deal with this constraints on usage by introducing flexibility. Generalized distributions were derived using the Generalized Pareto Distribution (GPD) as base distribution. Exponentiated GPDs called Lehmann Type II GPD (LIIGPD) and Lehmann Type I GPD (LIGPD) having an additional parameter each were obtained by applying Lehmann Alternative 1 (LA1) and Lehmann Alternative 2 (LA2) parameter induction methods respectively. Flexibility of generalized distributions was established by comparing the shapes of probability density and hazard functions of LIIGPD and LIGPD with those of the GPD. No new probability density or hazard shape was introduced by LIIGPD but the new shape introduced by LIGPD demonstrated flexibility of generalized distributions. Generalized distributions do not always introduce new density and hazard shapes but often improve flexibility of distributions.Item Food taboos among pregnant Nigerian Women in Ilorin.(Unilorin, 2014) Olarinoye, Adebunmi; Adesina, Kikelomo; Olarinoye, John; Adejumo, Adebowale; Ezeoke, GraceBackground: Myths and taboos play an important role in the lives of women in the area as in other parts of the world. Some taboos can be dysfunctional or harmful. Objectives: To examine food taboos related to pregnancy and their perception by the women. Methods: There were 275 respondents through use of questionnaires applied at antenatal clinics. Results: Mean age was 29.08 years. 192(72%) of the respondent had tertiary levels of education and 32% to 75% were not in agreement with the food taboos and the possible negative effects attached. In the taboo associated with avoidance of caffeinated drink, there was a greater proportion in agreement 49% compared to 32%. Conclusion: Belief and adherence to food taboos is reducing in our environment as a result of increase in level of education, occupation and urbanization. No significant negative effect on past pregnancy outcomes was observed. Change should be approached in form of educating the women. This can be done during the health talks given by the nurses during antenatal visits and more importantly through increase in formal education especially to higher levels.Item Goodness of Fit Tests for Some Generalized Distributions(Federal University Wukari, Taraba State, Nigeria, 2020-04) Omekam, Ifeyinwa; Adejumo, AdebowaleAnalysis of data without a pre-knowledge of the distribution that describes data may lead to misleading or irrelevant result. Distribution fitting to data often lead to the selection of the best fitting distribution for data analysis. In this article, some existing distributions are fitted to Maternal Mortality Ratio (MMR) data. Using the best fitting distribution obtained as base distribution, generalized distributions having additional parameters are then derived and subsequently fitted to MMR to assess goodness of fit. Generalized distributions improved goodness of fit.Item Modified Frechet Distributions and Their Generalized Families(Faculty of Science, Kaduna State University, 2022-07-10) Omekam, Ifeyinwa; Adeniyi, Olakitan; Adejumo, AdebowaleThe Frechet distribution is used for modeling extreme events. There are different approaches to developing statistical distributions which include the use of translation methods, system of differential equations, quantile methods among others. Existing statistical distributions are also modified or generalized to accommodate other different types of data and improve goodness of fit to data. Addition of extra parameter(s) is one approach used for generalizing existing distributions such that the base distributions are embedded in the new generalized distributions. Some methods of parameter induction were used to obtained families of generalized distributions. Parameter(s) were also introduced into the probability distributions of the Frechet distribution to derive functions of its modified versions belonging to each of the generalized families derived. Further study is recommended on some of the modified Frechet distributions and their generalized families.Item Some Extended Pareto type I Distributions(Obafemi Awolowo University, Ife, Osun State, Nigeria under the platform of Africans Journals Online, 2022-10-13) Omekam, Ifeyinwa; Popoola, Jumoke; Gatta, Nusirat; Adejumo, AdebowaleProbability distributions are essential in data modeling. Introduction of parameter(s) into existing probability distributions is a method of extending or generalizing distributions to produce more flexible distributions and for better fit to data. The Pareto type 1 distribution (PT1) is a right skewed continuous distribution originally used in description of wealth and income but also used for modeling other right skewed data. To add flexibility, Pareto type 1 distribution was extended by introducing parameter(s) into its probability distribution to accommodate more types of data. Some functions of the extended Pareto type 1 distributions were derived using five parameter induction methods. Flexibility of extended distributions was demonstrated through comparisons of density and hazard function shapes of some of the extended distributions with those of the PT1. Further study on properties of non-existing extended Pareto Type I distributions and real-life applications are recommended.