Browsing by Author "Aderoju, S. A"

Now showing 1 - 3 of 3
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    On Zero-Truncated Negative Binomial with Excess Ones
    (Asian Journal of Probability and Statistics, 2023-05-11) Jolayemi, E.T.; Aderoju, S. A
    In this paper, Zero-truncated negative binomial distribution is modified to include excess ones to improve goodness-of-fit. This is necessary when data are dispersed and zero has been eliminated from data structurally. However, when the ones are unduly large, the proportion of this excess must be recognized and estimated to improve the fit. This development is applied using real data from a national survey.
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    Power Samade distribution: its properties and application to real lifetime data
    (Nigerian Journal of Science and Environment, 2023-06-16) Aderoju, S. A; Babaniyi, O.
    A new three parameter lifetime distribution has been introduced in this research work by using Gamma generalized family of distributions. The density, survival, and hazard functions of the proposed Power Samade distribution were derived and discussed. Its mathematical properties were derived. The maximum likelihood method of estimation was used to estimate its parameters. Three lifetime data sets were used to assess the performance of the proposed distribution. Our finding revealed that the Power Samade distribution suited all the data sets compared to the other competing distributions as it has a maximum value of loglikelihood and least values of statistic criteria including AIC, AICC and BIC.
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    Towards malaria elimination: analysis of travel history and case forecasting using the SARIMA model in Limpopo Province
    (Parasitology Research (Springer), 2023-06-13) Oyegoke, O.O.; Adewumi, T.S.; Aderoju, S. A; Tsundzukani, N.; Mabunda, E.; Adeleke, M.A.; Maharaj, R.; Okpeku, M.
    Despite various efforts and policy implementation aimed at controlling and eliminating malaria, imported malaria remains a major factor posing challenges in places that have made progress in malaria elimination. The persistence of malaria in Limpopo Province has largely been attributed to imported cases, thus reducing the pace of achieving the malaria-free target by 2025. Data from the Limpopo Malaria Surveillance Database System (2010–2020) was analyzed, and a seasonal autoregressive integrated moving average (SARIMA) model was developed to forecast malaria incidence based on the incidence data’s temporal autocorrelation. The study found that out of 57,288 people that were tested, 51,819 (90.5%) cases were local while 5469 (9.5%) cases were imported. Mozambique (44.9%), Zimbabwe (35.7%), and Ethiopia (8.5%) were the highest contributors of imported cases. The month of January recorded the highest incidence of cases while the least was in August. Analysis of the yearly figures showed an increasing trend and seasonal variation of recorded malaria cases. The SARIMA (3,1,1) X (3,1,0) [12] model used in predicting expected malaria case incidences for three consecutive years showed a decline in malaria incidences. The study demonstrated that imported malaria accounted for 9.5% of all cases. There is a need to refocus on health education campaigns on malaria prevention methods and strengthening of indoor residual spray programs. Bodies collaborating toward malaria elimination in the Southern Africa region need to ensure a practical delivery of the objectives.