Prof. Adebowale Olusola Adejumo
@unilorin.edu.ng
Professor, Statistics/ Physical Sciences
University of Ilorin
Adebowale Olusola Adejumo is a Professor in the Department of Statistics, Faculty of Physical Sciences, University of Ilorin, with over 24 years university teaching, research and administrative experience. He has served as the Head of Department and he is the current Faculty Representative in the Postgraduate Board of University of Ilorin. His area of specialization is Statistical Modeling, Biostatistics, Time series and Categorical Data Analysis. He has over ninety national and international publications in reputable outlets covering academic journals, Chapters in books, books, and technical reports and has sole supervised over eighty Masters Dissertations and ten Ph. D. Theses. Prof. Adejumo holds both B.Sc. and M.Sc. degrees in Statistics from University of Ilorin and Ph. D. degree (Dr. rer. nat) in Statistics from Ludwig Maximilians University, Munich, Germany. He is a member of many Professional bodies within and outside Nigeria.
EDUCATION
Ph. D. in Statistics, Ludwig Maximilian University, Munich, Germany
M. SC. in Statistics, University of Ilorin, Ilorin, Nigeria
B. SC. in Statistics, University of Ilorin, Ilorin, Nigeria
RESEARCH, TEACHING, or OTHER INTERESTS
Statistics and Probability, Statistics, Probability and Uncertainty, Modeling and Simulation, Statistics and Probability
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
A Ademola Adetunji, A. Justus Ademuyiwa, G. Nihinlolawa Alo, and A. Olusola Adejumo
Springer Science and Business Media LLC
Hilary I. Okagbue, Pelumi E. Oguntunde, Patience I. Adamu, and Adebowale O. Adejumo
Springer Science and Business Media LLC
Kayode Ayinde, Hamidu Abimbola Bello, Rauf Ibrahim Rauf, Omokova Mary Attah, Ugochinyere Ihuoma Nwosu, Oluwatoyin Kikelomo Bodunwa, Oluwadare Olatunde Ojo, Roseline Oluwaseun Ogundokun, Taiwo Stephen Fayose, Rasaki Yinka Akinbo,et al.
Springer International Publishing
Oluwole A Odetunmibi, Adebowale O Adejumo, and Timothy A Anake
IOP Publishing
Abstract Hepatitis B is caused by the hepatitis B virus (HBV) and it affects livers. It has been established that the disease is a serious medical condition caused by an overpowering immune response to infection. To this effect, there is a need for cross examination of records of patients on this disease to ascertain the factors that could be responsible for the survival or dying from this disease. Descriptive analysis of the data showed that sexually active age bracket (31 – 50) are greatly affected by the disease while female accounted for majority of those that are tested positive to the disease. Chi squared statistic was used to test for independence between age and gender of those who tested positive to disease between 2006 and 2015 in Lagos state, Nigeria. It was discovered that, both variables of age and gender are not independent which means there is association between the Age and Gender of HBV patients.
Oluwole A. Odetunmibi, Adebowale O. Adejumo, and Timothy A. Anake
Scientific Foundation SPIROSKI
BACKGROUND: The effect of age and gender on the transmission of any infectious disease can be of great important because the age at which the host contact the disease may be a determinant on the rate at which the disease will spread.
 AIM: The purpose of this research is to model the significant effect of age and gender on the spread of hepatitis B virus using data collected from Lagos State, Nigeria.
 MATERIAL AND METHODS: The data that was used for this research is a ten years data covering the period of 2006 to 2015, which was collected from Nigeria Institute of Medical Research (NIMR). A log-linear modelling approach was employed using R programming language software. Akaike Information Criterion (AIC) method of model selection was used in selecting the best model.
 RESULTS: It was discovered from the analysis that both factors (age and gender) have a significant effect on the spread of hepatitis B infection. This means that the age at which an individual is tested positive to hepatitis B virus will affect the spread of the disease. In choosing the best model among the four models that were developed, model AY: GY (age & year: gender and year) was found to be the best model.
 CONCLUSION: Age and gender were found to act as a risk influencer that could have a great effect on the transmission of hepatitis B virus infections in Lagos state, Nigeria.
Pelumi E. Oguntunde, Oluyemisi A. Adejumo, Oluwole A. Odetunmibi, Hilary I. Okagbue, and Adebowale O. Adejumo
Elsevier BV
Adebowale O. Adejumo, Esivue A. Suleiman, Hilary I. Okagbue, Pelumi E. Oguntunde, and Oluwole A. Odetunmibi
Elsevier BV
Oluwole A. Odetunmibi, Oluyemisi A. Adejumo, Pelumi E. Oguntunde, Hilary I. Okagbue, Adebowale O. Adejumo, and Esivue A. Suleiman
Elsevier BV
Pelumi E. Oguntunde, Adebowale O. Adejumo, and Hilary I. Okagbue
Elsevier BV
Adebowale O. Adejumo, Nehemiah A. Ikoba, Esivue A. Suleiman, Hilary I. Okagbue, Pelumi E. Oguntunde, Oluwole A. Odetunmibi, and Obalowu Job
Elsevier BV
Adebowale O. Adejumo, Esivue A. Suleiman, and Hilary I. Okagbue
Elsevier BV
Pelumi Emmanuel Oguntunde, Adebowale Olusola Adejumo, and Enahoro Alfred Owoloko
Science Alert
Pelumi E. Oguntunde, Mundher A. Khaleel, Mohammed T. Ahmed, Adebowale O. Adejumo, and Oluwole A. Odetunmibi
Hindawi Limited
Developing new compound distributions which are more flexible than the existing distributions have become the new trend in distribution theory. In this present study, the Lomax distribution was extended using the Gompertz family of distribution, its resulting densities and statistical properties were carefully derived, and the method of maximum likelihood estimation was proposed in estimating the model parameters. A simulation study to assess the performance of the parameters of Gompertz Lomax distribution was provided and an application to real life data was provided to assess the potentials of the newly derived distribution. Excerpt from the analysis indicates that the Gompertz Lomax distribution performed better than the Beta Lomax distribution, Weibull Lomax distribution, and Kumaraswamy Lomax distribution.
Enahoro Alfred Owoloko, Pelumi Emmanuel Oguntunde, and Adebowale Olusola Adejumo
Science Publications
In this article, the convoluted exponential distribution which was derived as the sum of two independent exponentially distributed random variables was compared with the exponential distribution in terms of flexibility when applied to four real data sets. The idea is to verify if the convoluted exponential distribution would perform better than the exponential distribution in modeling real life situations. Some other basic statistical properties of the convoluted exponential distribution were also identified.
P. E. Oguntunde, O. A. Odetunmibi, and A. O. Adejumo
Indian Society for Education and Environment
Background/Objectives: In this article, a generalization of the Weibull distribution is being studied in some details. The new model is referred to as the Exponentiated Generalized Weibull distribution. The aim is to increase the flexibility of the Weibull distribution. Methods: The concepts introduced in the Exponentiated Generalized family of distributions due to Cordeiro et al.11 were employed. Findings: Some basic mathematical properties of the resulting model were identified and studied in minute details. Meanwhile, estimation of model parameters was performed using the maximum likelihood method. Application/Improvement: The Exponentiated Generalized Weibull distribution was presented as a competitive model that would be useful in modeling real life situations with inverted bathtub failure rates. The R-code for the plots was also provided. Further research would involve applying the proposed model to real life data sets.
Enahoro A. Owoloko, Pelumi E. Oguntunde, and Adebowale O. Adejumo
Springer Science and Business Media LLC
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
CONSULTANCY
National Mathematical Centre, Abuja, Nigeria