DSpace Angular :: Browsing by Author "Aderoju, S.A."

Browsing by Author "Aderoju, S.A."

Now showing 1 - 13 of 13

A Comparative Study on Zero-truncated Generalized Poisson-Lindley and Zero-truncated Poisson-Lindley Distributions
(International journal of Mathematical Archive (IJMA), 2017) Aderoju, S.A.; Jolayemi, E.T.; Ibrahim, A.O.
In this paper, Zero-truncated Com-binomial distribution was derived and investigated its behavior in modeling structurally non-zero data. The proposed distribution is characterized by two parameters, which make it flexible. The maximum likelihood method is used to obtain the estimators of the parameters through R-software. Two real-life datasets were used to evaluate its performance. The statistic (chi square goodness-of-fit) with the p-value shows that the proposed Zero-truncated Com-binomial distribution yields “a good fit”.
A new generalized Poisson mixed distribution and its application
(Applied Mathematical Sciences, 2020) Aderoju, S.A.
A new generalized Poisson mixed distribution is proposed in this study called New Generalized Poisson-Sujatha distribution (NGPSD). The properties and application of the distribution are studied. The two parameter distribution is obtained by compounding Poisson distribution with a two parameter generalized Sujatha distribution. The distribution has a tendency to account for over-dispersion in count data. The first four moments, variance and coefficient of variation of the distribution are also obtained. The estimators of its parameters are obtained via maximum likelihood method using R-software. The goodness-of-fit of the distribution is compared with other distributions such as Poisson distribution (PO), negative binomial (NB), Generalized Poisson-Lindley (GPL) and a New Generalized Poisson-Lindley (NGPL) Distributions. It can be seen that the test statistic, AIC and BIC for the NGPSD are lower than those of competing distributions implying that the proposed distribution satisfactorily fits better to the data set.
Covid 19: Determination of the Relationship between Sex, Having Handkerchief or Staying Indoor and Facial Touch
(International Journal of TROPICAL DISEASE & Health, 2020-05-23) Aderoju, S.A.; Ajewole, S.S.; Balogun, O.S.
Background: Covid-19 outbreak is the current pandemic confronting nations in the world. The virus had caused so much loss of lives, loss of jobs and serious damages to global economy. One major way of preventing the spread of the virus and guide against being infected is to avoid face touching with unwashed hand(s). Objective: The objective of this study is to investigate the association between sex, having handkerchief or staying indoor and number of time a person touches face (mouth, eyes or nose). Methodology: A sample size of n = 130 people were randomly selected and observed obliviously for 120 seconds. The number of times they touched their faces were recorded with other variables like sex, having handkerchief and staying indoor or outdoor. Since the response variable is count, appropriate models for such data were used. Results and Conclusion: The Poisson results shown that there exist overdispersion, hence, a model that can account for the dispersion parameter was used to obtain accurate results. The results of the analysis shown that there is no association between the number of time a person touches face and sex, having handkerchief or staying indoor. The expected number time people touch their faces within 120 seconds is twice while the minimum and maximum number of times are zero and eight respectively. Recommendation: It is recommended that there ought to be adequate public enlightenment and sensitization on the peril of the novel COVID-19 pandemic and the reason why individuals ought to stick carefully to the exhortation of abstaining from touching of faces (without washing with soap and water) so as to forestall its spread. If a person's hands are contaminated with the virus, he/she isn't infected until he/she touches the face (nose, eye or mouth) with the hands unwashed.
Effectiveness of Fiscal Federalism for Poverty Reduction in Nigeria: An Analysis of Federal and State Governments’ Expenditures
(SN Business & Economics, 2021) Megbowon, E.T.; Aderoju, S.A.; Sanusi, G.
Abstract One of the sustained political and economic strategies that have been adopted by various countries over three decades to achieve the desired level of development is fiscal federalism. Through this economic development strategy, various levels of government within an economy have been involved in the pursuit of reducing poverty over the decades. The purpose of this study is to examine the relationship between government expenditure on poverty reduction with respect to federal and state government expenditures respectively. The study employed the auto-regressive distributed lag (ARDL) estimation technique to establish long-run relationship, and to examine the magnitude of the effect of federal and state government expenditures in both the short-run and long-run periods using time-series data for the period 1981 to 2018. Results obtained indicate that only state government expenditure has positive effect on poverty reduction in Nigeria. The findings of this study therefore support the need for greater decentralization and increase in fiscal expenditure responsibilities and strengthening revenue capability in favor of state governments, giving that achieving desired poverty reduction could be achieved through increased state government spending.JEL Classification: E62, H50, I30
Issues of Class Imbalance in Classification of Binary Data: A Review
(International Journal of Data Science and Analysis, 2019) Aderoju, S.A.; Jolayemi, E.T.
Handling classification issues of class imbalance data has gained attentions of researchers in the last few years. Class imbalance problem evolves when one of two classes has more sample than the other class. The class with more sample is called major class while the other one is referred to as minor class. The most classification or predicting models are more focusing on classifying or predicting the major class correctly, ignoring the minor class. In this paper, various data pre-processing approaches to improve accuracy of the models were reviewed with application to terminated pregnancy data. The data were extracted from the 2013 Nigeria Demographic and Health Survey (NDHS). The response variable is “terminated pregnancy” (asking women of reproductive age whether they have ever experienced terminated pregnancy or not), which has two possible classes (“YES” or “NO”) that exhibited class imbalanced. The major class (“NO”) is 86.82% (of the sample) representing Nigerian women of age 15 – 49 years who had never experience terminated pregnancy while the other category (minor class) is 13.18%. Hence, different resampling techniques were exploited to handle the problem and to improve the model performance. Synthetic Minority Oversampling Technique (SMOTE) improved the model best among the resampling techniques considered. The following socio-demographic factors: age, age at first birth, residential area, region, education level of women were significantly associated with having terminated pregnancy in Nigeria.
Modeling of Tuberculosis and Tuberculosis Co-infected with Human Immunodeficiency Virus Patents using some Parametric Survival Models
(The Pacific Journal of Science and Technology, 2020) Olaosebikan, A.; Aderoju, S.A.; Balogun, O.S.
In this study, the authors examined age and gender as some of the challenges of modeling infectious diseases using data comprising of patients with Tuberculosis (TB) and TB coinfected Human Immunodeficiency Virus (HIV) as a case study. The TB and TB co-infected with HIV are some of the common health problems in the world. Time-to-event outcomes are common data types in medical research. The data examined time until a patient is cured of the disease having some patients right-censored. With the nature of the data, the appropriate analysis is the survival analysis method. The study aims at fitting appropriate models to the TB and TB/HIV coinfection data examining age and gender as factors influencing the survival of the disease. Hence, Kaplan-Meier estimation, Cox PH and some parametric models were adopted in the study. The result shows that among the parametric models, generalized gamma fit TB data best and there is a significant difference in the survival rate of male and female while Cox model fit TB coinfected with HIV best and there is a significant difference in the male and female patient. The median survival times are 17 and 18 months for TB patients and TB/HIV co-infected patients respectively.
Modelling Of Accident Data In Nigeria: Poisson And Poisson Gamma Regressio
(2015) Aderoju, S.A.; Jolayemi, E.T.
Poisson and Poisson-gamma (Negative Binomial) regression models belong to the group of generalized linear models that are suitable to model count data. While the two regression types often give similar results, there can be differences in the effects of the covariates they estimated depending on weather the data is equi-dispersed, over-dispersed or under-dispersed. This work therefore demonstrates the behaviours of Poisson and Poisson-gamma regression models when the data is overdispersed (variance greater than the mean). The two regression types were employed to model the number of people killed in road accidents as a function of the number of fatal, serious and minor accidents that occurred. Results from the two regression models indicated that number of people killed in road accidents is determined majorly by the number of fatal and serious cases of road accidents that occurred and not really by the number of minor accidents. The differences in the two regression models are described in the light of the over-dispersion in the data and the ability of the models to account for it. Road accident data of Kwara State, Nigeria for nine consecutive years from 2000 to 2008, primarily collected by the Nigeria Police Force (NPF), were employed in this study.
On modeling Zero-truncated count data
(Journal of Global Research in Mathematical Archives, 2018) Aderoju, S.A.; Jolayemi, E.T.
In this paper, a more generalized zero-truncated distribution that come from the mixture of distributions was developed and implemented for non-zero count data. The application of the distribution was demonstrated and its performance assessed against some existing ones using real life datasets. Following the idea of mixed distributions, the Zero-Truncated Com-Binomial (ZTCB) is from the mixture of Conway-Maxwell-Poisson type generalization to the Binomial distribution. The first two moments via probability generating function were also derived. The Maximum Likelihood Estimations of the parameters were also obtained by direct maximization of the log-likelihood function using “optim” routine in R software. The findings of the study showed that: the ZTCB distribution is more robust to handle all levels of dispersion than Zero-Truncated Multiplicative Binomial distribution. The statistics (chi square goodness-of-fit) as well as Deviance (in example four) and the AIC show that the proposed ZTCB distribution yields best result among the models under consideration. This paper therefore provides useful alternative to the existing zero-truncated distributions.
On Poisson-Samade Distribution: Its Applications in Modelling Count Data
(Earthline Journal of Mathematical Sciences, 2023-05-07) Aderoju, S.A.; Adeniyi, I.; Olaifa, J.B.; Olaosebikan, A.
A new mixed Poisson model is proposed as a better alternative for modelling count data in the presence of overdispersion and/or heavy-tail. The mathematical properties of the model were derived. The maximum likelihood estimation method is employed to estimate the model’s parameters and its applications to the three real data sets discussed. The model is used to model sets of frequencies that have been used in different literature on the subject. The results of the new model were compared with Poisson, Negative Binomial and Generalized Poisson-Sujatha distributions (POD, NBD and GPSD, respectively). The parameter estimates expected frequencies and the goodness-of-fit statistics under each model are computed using R software. The results show that the proposed PSD fits better than POD, NBD and GPSD for all the data sets considered. Hence, PSD is a better alternative provided to model count data exhibiting overdispersion property.
Power Hamza distribution and its applications to model survival time
(Journal of the Nigerian Statistical Association, 2022) Aderoju, S.A.; Jolayemi, E.T.
In this paper, a new lifetime model for survival time analysis has been introduced, which is called power Hamza distribution (PHD) that generalizes the Hamza distribution. Some properties of the new distribution, including the probability density function, cumulative distribution function, moments, failure rate function or hazard function and moments were presented. The model provides more flexibility than the Lindley and Hamza distributions in terms of the shape of the density and hazard rate functions. Estimate of the model parameters were obtained via the method of maximum likelihood and applications of the model were made to two real data sets. By using some criteria like Akaike Information criteria (AIC) and Bayesian Information Criteria (BIC) and other statistic, the PHD model provides better fits than other classical lifetime models such as Hamza, exponential and Lindley distributions.
Samade Probability Distribution: Its Properties and Application to Real Lifetime Data
(Asian Journal of Probability and Statistics, 2021-07-19) Aderoju, S.A.
A new two-parameter lifetime distribution has been proposed in this study. The distribution is called Samade distribution. The model is motivated by the wide use of the lifetime models derived from the mixture of gamma and exponential distributions. Its mathematical properties which include the first four moments, variance as well as coefficient of variation, reliability function, hazard function, survival function, Renyi entropy measure and distribution of order statistics have been successfully derived. The maximum likelihood estimation of its parameters and application to real life data have been discussed. Application of this model to three real datasets shown that the proposed model yields a satisfactorily better fit than other existing lifetime distributions. The comparism of goodness-of-fits were established using -2Loglikelihood, AIC and BIC.
The Relationship between Socio demographic Factors and Terminated Pregnancy among Nigerian Women
(Australian Journal of Basic and Applied Sciences, 2019) Aderoju, S.A.
Background: Pregnancy termination is an illegal medical procedure in Nigeria except in a situation of having the child puts the mother’s life at risk. Hence, the act is a rare event in the country and associated with some sociodemographic factors. Objective: The aims of the study were to appropriately model pregnancy termination so as to evaluate sociodemographic factors contributing to having terminated pregnancy among Nigerian women. Methods: The data were extracted from the 2013 Nigeria Demographic and Health Survey (NDHS) which exhibited class imbalanced, hence, logistic regression in large rare events and imbalanced data using different resampling techniques were exploited to improve the model’s performance. Synthetic Minority Oversampling Technique (SMOTE) function was used to improve the model’s performance. The analysis was done using R software. Results: The results showed that the model’s sensitivity and Precision values improved from zero to 50% and 32.43% respectively; this aspect is missing in the previous literatures to the best of my knowledge. Keeping other factors constant, a unit increase in age the odds of having pregnancy termination increases by 3.6%; women living in urban area were 50% more likely to experience pregnancy termination than women living in rural area; women from North East (NE), North West (NW), South East (SE), South South (SS) and South West (SW) were 83.5%, 22.5%, 43.2%, 25.3% and 25.9% , respectively, more likely to experience pregnancy termination than women from North Central (NC); women with primary, secondary and higher education levels were 39.2%, 50.1% and 44%, respectively, more likely to experience pregnancy termination compared to women with no education. Conclusion: The findings of this study shows that in using predictive model, there is need to evaluate the model’s accuracy, sensitivity and precision in order to ascertain the reliability of the model’s results. Moreover, family planning projects in Nigeria should stress on advancing the use of modern preventative techniques to further reduce the cases of pregnancy termination. Above all, there is need to improve maternal healthcare services in order to help women during the difficulties of unintended pregnancy
Zero-Truncated Compoisson-Binomial Distribution and its Application
(International Journal of Advanced Research in Science, Engineering and Technology, 2017) Aderoju, S.A.
In this paper, Zero-truncated Com-binomial distribution was derived and investigated its behavior in modeling structurally non-zero data. The proposed distribution is characterized by two parameters, which make it flexible. The maximum likelihood method is used to obtain the estimators of the parameters through R-software. Two real-life datasets were used to evaluate its performance. The statistic (chi square goodness-of-fit) with the p-value shows that the proposed Zero-truncated Com-binomial distribution yields “a good fit”.

Browsing by Author "Aderoju, S.A."

Results Per Page

Sort Options