4 peer-reviewed journal publications in statistical distribution theory, biomedical science, and applied mathematics. Published in indexed international journals through the American Journal of Biomedical Science and Research, Journal of Advances in Applied Mathematics, and Asian Journal of Advanced Research and Reports.
Introduces a new generalised family of the Inverse Lomax distribution and derives closed-form expressions for its statistical properties including the hazard rate function, moment generating function, and quantile function. Maximum likelihood estimation with asymptotic confidence intervals is applied to 3 real-world lifetime datasets, demonstrating superior fit compared to the Weibull, Gamma, and Log-normal distributions under AIC, BIC, and HQIC criteria.
Presents a comparative analytical framework for selecting among four exponential-based compound continuous distributions. The paper provides model selection criteria using AIC, BIC, and goodness-of-fit tests applied to both simulated and real-world datasets, with practical guidance for applied statisticians on distribution selection under different data characteristics.
Proposes a new generalisation of the length biased exponential distribution. The paper derives statistical properties including moments, reliability measures, and order statistics, and demonstrates applications to engineering and biomedical reliability data, showing improved fit over the standard exponential and its existing generalisations.
An epidemiological prevalence study of lung cancer applying logistic regression and chi-square analysis to clinical data. Identifies significant associations between tobacco exposure, occupational risk factors, and lung cancer incidence. Provides statistical inference for prevalence estimation with 95% confidence intervals, contributing evidence-based findings for public health policy in the Nigerian context.
Open to co-authorship on projects involving Bayesian methods, survival analysis, financial econometrics, NLP, and applied machine learning. Contact with a research proposal.
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