Dr. Oyamakin's Research

(a) COMPLETED

(i). Monte- Carlo Study of Asymptotic properties of Simultaneous Equation Estimators of correlated random deviates.

(ii). Forestry Research Institute of Nigeria BIODATA analysis for GAP using Staff Distribution in terms of Gender, Area of Specialization, Educational Qualification, Promotion and Appointments.

(iii). Development of Alternative Nonlinear Growth Models for Biological Processes based on Hyperbolic Sine Function.

(b) CURRENT RESEARCH

My research interest has been majorly on statistical modeling with special interest to the development of nonlinear hyperbolic growth models for biological processes. Growth been a biological phenomenon with respect to time is important in understanding many biological entities. Modeling it plays an important role in the study of biological processes. My research aimed at reparametizing the Malthusian Growth Equations and its variants by convoluting the hyperbolic sine function on growth equations to enhance internal prediction of biological entities through valid comparison. Weight of Japanese Quail; Coturnix coturnix L. (JQ) and Malaysian Oil Palm Fresh Fruit Bunches (MOPFFB), Top Height (NTH) from a Norwegian thinning experiment, sample plot 3661, Gmelina arborea Roxb. (GH), Pine (Pinus caribaea Morelet) (PH) and the diameter at breast height of Pine (Pinus caribaea Morelet) (PDBH) from organisations have been used to test the validity of the new models in terms of general fitness and internal predictive status as well as robustness. Some other areas of research that is a bit diverse is also been considered example of which are human population predictions through intercensal and postcensal projections. Furthermore, studies are ongoing in the development of new models based on hyperbolic tangent especially for systems where growth rate is slow and measurable only at long intervals. A special consideration is also given to infectious disease modeling while looking at other areas of research in Public health

(c) IN PROGRESS

1. Comparative assessment of Forest Gap models using statistical distributions.

The description, understanding and prediction of the long-term dynamics of forest ecosystems have fascinated ecologists for a long time. In spite of this, quantitative theories of forest dynamics are difficult to construct because of an inadequate database on long-term processes, their environmental influences, associated feedback mechanisms, and the lack of tools to synthesize the available knowledge. This study provided an extension to gaps using statistical distributions. This was achieved by representing deforested areas (Holes: Through aerial surveillance) in a natural forest as a probability distribution say , the likelihood and maximum likelihood of these distributions were obtained with a view to compare this method with the existing gap models in other to recover the vegetative cover and control the rate at which top soils are exposed to direct sunlight.

2. Population Dynamics in Nigeria using Hyperbolic Sine Function induced restrictions
Population projections using improved dynamics with application to Nigeria population structures are very important for nation building. Hence, this study involves developing models for determining the population trends in Nigeria. We started this by developing deterministic models capable of mimicking the rates at which we increase as a nation, hyperbolic sine function was used in creating bounds for existing exponential equation so as to serve as a better way of predicting future population values for long term planning. The developed models would be compared with the existing ones so as to validate its usefulness in predicting future population values.

3. Development of Statistical indices for the computation of Above ground biomass.

The first aspect of this work was done in 2013 and presented at the 13^th Bi-Annual conference of the Sub-Saharan African network (SUSAN) of International biometrics society (IBS) in Ghana, where we computed and subjected the above ground biomass of eight tree species to statistical distribution test and came up with Weibull as the best statistical distribution for above ground biomass. We intend to improve on this by developing an index through which this can be computed without going through the various steps available in literature. This would be of greater importance to the implementation of REDD+ in Nigeria.

4. Dredging into the health and wellbeing of Adolescents in Southwestern Nigeria: A Baseline survey.
Public Health studies on Adolescent health, Infectious diseases modelling and Modified Quarantine modelling: This is an on-going work of the Africa Research, Implementation Science and Education (ARISE) Network of Harvard T. H. Chan School of Public Health in which University of Ibadan Research Foundation is a partner and I am a Mentee. This study is meant provide a baseline data as well as use statistical modelling tools to identify the critical aspects that have greater effect on the wellbeing of the adolescent with the overall goal of producing necessary data useful for the management and design of program interventions as well as in improving the lives of adolescents in the study population.

5. Allele evolution and extinction modelling, Modelling Gene-geneprotein network topologies and genotype by environment inferences.

6. Mathematical/Statistical modelling of emerging infectious diseases

7. Sensitivity of Genotype by Environment Interaction Models to outlying observation.

(d) DISSERTATION AND THESIS

(i) Oyamakin S.O. (2002): Index number of some subscribers to Nigeria telecommunication Limited Osogbo. National Diploma Project Submitted to the Department of Statistics, Osun State Polytechnic, Iree, Osun State, Nigeria.

(ii) Oyamakin S.O. (2006): Childhood Malnutrition in Nigeria- A case study of Oje community in Ibadan, Oyo State. B.Sc. Project, Department of Statistics, University of Ibadan.

(iii) Oyamakin S.O. (2010): Sensitivity of Simultaneous Equation Techniques to varying correlation coefficients. M.Sc. Thesis, Department of Statistics, University of Ibadan.

(iv) Oyamakin S.O. (2015): Development of Alternative Nonlinear Growth Models for Biological Processes Based on Hyperbolic Sine Function. Ph.D. Thesis, Department of Statistics, University of Ibadan. (Published: https://www.amazon.com/Alternative-Nonlinear-Growth-Biological-Processe…;

(e) HONOURS, AWARDS AND DISTINCTIONS

i. Chartered Statistician (CStat.), Royal Statistical Society (RSS), London. 2014

ii. Chartered Scientist (CSci.), Royal Statistical Society (RSS), London. 2014

iii. Tet Fund Research grant to attend XIII International Conference on Energy, Ecology, Environment and Sustainable Development (ICEEESD 2015) by World Academy of Science, Engineering and Technology (WASET) held at Holiday Inn, Miami Beach, Florida, USA. 9^th – 10^th March. 2015.

iv. World Bank Funding to attend ISI2017 Marrakech, 61^st International Statistical Institute (ISI) World Statistics Congress, Marrakech, Morocco, 16 – 21 July, 2017.

v. Support grant to attend the Royal Statistical Society Conference 2017, University of Strathclyde, Glasgow, United Kingdom.

vi. ISI/IBS Ambassador’s award to attend International Biometric Conference 2018 in Barcelona, Spain between July 7^th – 14^th, 2018.

(a) Completed

(i). Monte- Carlo Study of Asymptotic properties of Simultaneous Equation Estimators of correlated random deviates.

(ii). Forestry Research Institute of Nigeria BIODATA analysis for GAP using Staff Distribution in terms of Gender, Area of Specialization, Educational Qualification, Promotion and Appointments.

(iii). Development of Alternative Nonlinear Growth Models fo Biological Processes based on Hyperbolic Sine Function.

(b) IN PROGRESS

Comparative assessment of Forest Gap models using statistical distributions.

Population Dynamics in Nigeria using Hyperbolic Sine Function induced restrictions

Development of Statistical indices for the computation of above ground biomass and carbon sequestration in modelling climate fluctuations

Dredging into the health and wellbeing of Adolescents in Southwestern Nigeria: A Baseline survey. In partnership with African Academy for Public Health (AAPH), Tanzania and Harvard T. H. Chan School of Public Health.

Allele evolution and extinction modelling, Modelling Gene-geneprotein network topologies and genotype by environment inferences.

Mathematical/Statistical modelling of emerging infectious diseases

Sensitivity of Genotype by Environment Interaction Models to outlying observation.

(c) DISSERTATION AND THESIS

(ii) Oyamakin S.O. (2006): Childhood Malnutrition in Nigeria- A case study of Oje community in Ibadan, Oyo State. B.Sc. Project, Department of Statistics, University of Ibadan.

(iii) Oyamakin S.O. (2010): Sensitivity of Simultaneous Equation Techniques to varying correlation coefficients. M.Sc. Thesis, Department of Statistics, University of Ibadan.

(d) HONOURS, AWARDS AND DISTINCTIONS

Chartered Statistician (CStat.), Royal Statistical Society (RSS), London. 2014
Chartered Scientist (CSci.), Royal Statistical Society (RSS), London. 2014
Tet Fund Research grant to attend XIII International Conference on Energy, Ecology, Environment and Sustainable Development (ICEEESD 2015) by World Academy of Science, Engineering and Technology (WASET) held at Holiday Inn, Miami Beach, Florida, USA. 9^th – 10^th March. 2015.
World Bank Funding to attend ISI2017 Marrakech, 61^st International Statistical Institute (ISI) World Statistics Congress, Marrakech, Morocco, 16 – 21 July, 2017.
500 GBP support grant to attend the Royal Statistical Society Conference 2017, University of Strathclyde, Glasgow, United Kingdom.
$5000 Grant ISI Ambassador’s award to attend International Biometric Conference 2018 in Barcelona, Spain between July 7^th – 14^th.