| 1 |
Author(s):
Ockiya Atto Kennedy, Orumie Ukamaka Cynthia, Emmanuel Oyinebifun.
Page No : 1-23
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Garch Models Comparison with Symmetric and Asymmetric Process for Univariate Econometric Series
Abstract
The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model was modeled using both symmetric and asymmetric processes. Secondary data from January 2005 to December 2021 on the Consumer Price Index, Exchange Rate, Crude Oil Price, and Inflation Rate were used for this study. The research was conducted using the statistical software packages Minitab and E-view. The aforementioned four macroeconomic variables show a tendency for volatility to cluster across time. In both symmetric and asymmetric processes, the volatility condition and leverage impact coefficients were present. By contrasting the symmetric models (ARCH, GARCH, and GARCH-M) and the asymmetric models, the best model was chosen using Akaike Information Criteria (E-GARCH, T-GARCH and APARCH). For the investigated univariate economic variables, the results indicated that the found asymmetric model GARCH models outperformed the symmetric model GARCH models. Therefore, these models can be applied to the forecasting of these series of economic indicators. Models include the Asymmetric E-GARCH (1, 1) Model for Consumer Price Index, Crude Oil Price, and Inflation Rate Series and the Asymmetric T-GARCH (1, 1) Model for Exchange Rate Series.
| 2 |
Author(s):
Ockiya Atto Kennedy, Orumie Ukamaka Cynthia, Emmanuel Oyinebifun.
Page No : 24-39
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Multivariate Garch Models Comparison in Terms of the Symmetric and Asymmetric Models
Abstract
Modelling the Multivariate Generalised Autoregressive Conditional Heteroscedasticity (GARCH) model included both symmetric and asymmetric processes. The information includes monthly data for the Consumer Price Index, Crude Oil Price, Exchange Rate, and Inflation Rate from January 2005 to December 2021. For the analysis, E-view Statistical software was employed. The aforementioned four macroeconomic variables show a tendency for volatility to cluster across time. Both symmetrical and asymmetrical processes had the volatility condition. The residual recursive plot was used to analyse the structural fluctuation in the series. The plot showed continual movement in the inflation rate as well as a downward and upward movement in the consumer price index, exchange rate, and crude oil price. The Akaike Information Criterion (AIC), Hannan-Quinn Information Criterion (HQIC), and Schwarz Information Criterion were chosen as the best models based on information criteria (SIC). Symmetric and asymmetric modelling techniques were used to create the Economic Variables Multivariate GARCH (M-GARCH) models. To calculate the covariance and correlation between the four variables, M-GARCH models were utilised. The main finding of the estimation of all M-GARCH models is that the symmetric models (Diagonal BEKK and Constant Conditional Correlation, or "CCC") have the lowest values of the model information criteria compared to the asymmetric models (Diagonal BEKK and CCC), while the asymmetric models (Diagonal VECH) have the lowest values of the model information criteria compared to the symmetric models (Diagonal VECH). Based on the findings, it was discovered that while analysing the interaction between the four economic variables returns series, the Symmetric Diagonal BEKK and CCC model outperformed the Asymmetric Diagonal VECH model.
| 3 |
Author(s):
Oti Eric U., Olusola Michael O., Alvan Wariebi K., Areh Onome C..
Page No : 40-50
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Effect of Effective Reading on Students’ Academic Performance in Tertiary Institution: A Case Study of Computer Science Department Federal Polytechnic, Ekowe Bayelsa State, Nigeria
Abstract
Academic performance is the measurement of students’ achievement across various academic subjects. Teachers and perhaps educationists measure academic achievements using classroom performance, graduation grades and results from standardized tests. In this paper, we carried out some statistical analysis to determine if the Grade Point Average (GPA) of students’ academic performance in Computer Science department 2020/2021 National Diploma (ND) one academic session, do depend on the number of hours students spend over the weekends reading their books using simple linear regression analysis and correlation analysis at 5 percent level of significance. The findings of the study shows that there is a linear relationship between the two variables y(GPA) and the number of x(hours) the students spent reading for their examinations, and it also indicates a strong significant difference on the effect of effective reading of students’ academic performance in tertiary institutions.
| 4 |
Author(s):
W.I.A. Okuyade, C.O. Aminobiren, T.M. Abbey.
Page No : 51-66
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Transient MHD Thermally Radiating Free Convective Flow Past an Exponentially Moving and Rotating Isothermal Vertical Plate with Heat Generation, Reacting Species and Fluctuating Mass Diffusion Effects
Abstract
The problem of transient MHD thermally radiating free convective flow past an exponentially moving and rotating isothermal vertical plate in the presence of heat generation reacting species, and fluctuating mass diffusion is examined. The flow is governed by a set of non-linear partial differential equations of the Boussinesq approximation type. In particular, the momentum equations are simplified using the 2-D fluid flow analysis in the complex plane, and the governing equations are solved using the time-dependent Homotopy Perturbation Method. Expressions for the concentration, temperature, and velocity are obtained and presented graphically. The results amidst others depict that an increase in the chemical reaction rate decreases the concentration, but causes fluctuation in the flow velocity structure; an increase in the Heat generation/absorption parameter increases the fluid temperature but causes fluctuation in the flow velocity structure.
| 5 |
Author(s):
Sojobi Olayiwola Adio, Olatayo Timothy Olabisi.
Page No : 67-79
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Spatial Analysis of Nigeria’s Presidential Election Based on Geographically Weighted Regression
Abstract
Geographically weighted regression (GWR) is a linear regression technique used to fit a regression equation to every observation in a dataset. In this study, both the global regression (multiple linear regression) and the GWR were calibrated for the 2019 Nigeria presidential election dataset, and diagnostics of each model were computed and compared. Experiments and analyses in the study were implemented in the R-environment, R-4.1.2. The GWR model outperforms the global regression model with an R^2 value of 0.776 exceeding that of the global regression of 0.513. The superiority of the GWR model is also confirmed by its much smaller RSS and AICc values (173.362 and 1372.8555 respectively), compared to those of the global regression (377.103 and 1662.316 respectively). The GWR model better fits the election dataset; it explains spatial variations in the dependent variable better than the global regression model does.
| 6 |
Author(s):
Ibrahim Ismaila Itopa, Alhaji Modu Isa, Sule Omeiza Bashiru.
Page No : 80-88
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Transmuted Topp-Leone Exponential Distribution: Theory and Application to Real Dataset
Abstract
The main aim of this study is to add to the existing literature on probability distributions. In this study, the transmutation map approach proposed by Shaw and Buckley (2007) was used to develop a probability distribution called Transmuted Topp-Leone Exponential (TTLE) distribution. The moment, moment generating function and entropy are among the statistical properties of the distribution that were derived. The maximum likelihood approach was used to estimate the parameters of the novel distribution. The TTLE distribution was applied to a real-world data set and compared to other well-known standard distributions; the result of the analysis revealed that the newly developed distribution is more superior than the competing models.
| 7 |
Author(s):
Omoloye M.A., Olatinwo M., Ayanlere O.F., Adesanya A.O., Emiola O.K.S., Umar A.M..
Page No : 89-109
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Determining Sensitive Parameters in the Transmission Dynamics of Malaria Disease Using Mathematical Model Approach
Abstract
The challenge posed by malaria disease calls for urgent need for a better understanding of important parameters in the disease transmission and development of prevention and control of the spread of malaria disease. In this work, a mathematical model for the dynamics of malaria disease is developed and analyzed. There is existence of disease free equilibrium and endemic equilibrium point of the model, the local stability of disease free equilibrium is obtained using Jacobian matrix which is locally asymptotically stable whenever the basic reproduction number is less than unity. Finally, the results obtained in Table 2, Figure 6 and Figure 8 from sensitivity analysis reveal that malaria disease can be control if biting rate of mosquito is eliminated in the population
| 8 |
Author(s):
Usoro Anthony E., Edeminam Desire Edeminam.
Page No : 110-137
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Analysis of Academic Staff Profiles for the Assessment of Productivity: A Case of Akwa Ibom State University, Nigeria
Abstract
Every educational institution requires a sufficient number of qualified academic staff to deliver on the mandate, which includes, training, research and community development service. The quality of academic staff in a tertiary institution is expected to reflect on its graduates, who should compete favourably in the world labour market and add value to the society. The motivation behind this research was predicated upon the need to assess the productivity of academic staff in Akwa Ibom State University. The aim was to analyse academic staff profiles for possible reclassification on the basis of some performance factors. Information about the qualification, years of experience and research publications for 388 pensionable academic staff of the university was obtained from staff records. Firstly, goodness of fit tests for conformity of academic staff mix with the NUC proportional distributions of 20%, 35% and 45% for Professors/Associate Professors, Senior Lecturers and Lecturer1/Below categories were conducted. The tests results showed conformity of 26 out of 38 departments with the NUC proportional staff mix. 12 departments were affected with non-conformity with the NUC proportional academic staff mix. This is a challenge, not only to the 12 affected departments, but to the university as a whole, and this calls for concern. Secondly, Fisher’s and Bayesian Discrminant methods were adopted to analyse the staff profiles for possible reclassification. The analysis using Fisher’s method has revealed 100% correct classification of Professors/Associate Professors, 71% correct classification of Senior Lecturers, 68% correct classification of Lecturer1/Below and overall correct classification and misclassification probabilities as 0.71 and 0.29 respectively. Bayesian method has recorded 100% correct classification of Professors/Associate Professors, 61% correct classification of Senior Lecturers, 88% correct classification of Lecturer1/Below and overall correct classification and misclassification probabilities as 0.84 and 0.16 respectively. Comparing the two approaches, there is a higher value of correct classification probability in Bayesian Discriminant approach than Fisher’s approach, and a lower misclassification probability in Bayesian method than Fisher’s method. Bayesian approach gives more advantage in minimizing the classification error than the Fisher’s linear Discriminant method, and therefore, places Bayesian Discriminant Approach on higher comparative advantage than Fisher’s Discriminant method. The classification and misclassification probabilities presented in this paper are modifications of Usoro (2015). This paper recommends Bayesian Discriminant Analysis, especially, when carrying out discriminant analysis involving many groups or populations to avert the multiple pairwise Fisher’s Linear Discriminant analysis for multiple sample or population distributions. The outcome of this research is a good working instrument for staff assessment, planning and development of academic manpower in Akwa Ibom State University.
