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All Journal African Multidisciplinary Journal of Sciences and Artificial Intelligence Kwaghe International Journal of Sciences and Technology
Idi D
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences

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Vector Autoregressive Modeling of Some Nigeria Inflation Factors Idi D; David I. J
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 1 No 1 (2024): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v1i1.3546

Abstract

This study investigates the modeling of some macroeconomic variables in Nigerian using multivariate monthly time series data from January 2010 to December 2019. The study examined two inflation factors which include money supply (MS) and exchange rate (ER) which are of great importance in determining inflationary effect in any economy. If MS is greater than ER then it can be said that the economy is experiencing rise in inflation and vice versa. Based on the analysis of implementing a vector autoregressive model to the data at stationarity using the Augmented Dickey–Fuller (ADF) test, Inflation rate (IR) was found to be significant only at lag 2 of IR. However, MS was found to be significant at lag 1 of ER and ER was significant at lag 1 and lag 2 of ER. The impulse response function plots clearly showed an unstable IR on MS and ER but at the later end of the periods, Nigeria IR tends towards a positive stability on MS and ER, respectively.
On the Application of Exponentiated Burr V Distribution and Its Extension Idi D; David I. J
Kwaghe International Journal of Sciences and Technology Vol 1 No 1 (2024): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v1i1.3574

Abstract

In this research, the application of Exponentiated Burr-V (EBV) distribution is presented and compared with other competing distributions which include Exponentiated Pareto distribution, Exponentiated Lomax distribution, Exponentiated Gumbel distribution, and Exponentiated Generalized Inverse Exponential distribution. The maximum likelihood estimation method was used in estimating the EBV and the four competing distributions. The loglikelihood (LL) and Akaike Information Criteria (AIC) was applied for determining the best fitted distribution and the distribution with the largest LL and smallest AIC is considered the best fitted distribution. The data used is on bladder cancer which is a widely used data from Lee and Wang (2003), Lemonte and Cordeiro (2011), Luz, (2012), and Kazeem et al., (2014). The results obtained showed that the EBV distribution has the largest LL value of 2950.726 and the smallest AIC value of –5895.452. The LL and AIC values imply that the EBV distribution is a very competitive distribution in fitting the bladder cancer data and it is an appropriate distribution for fitting asymmetric or negatively skewed and high kurtosis datasets.
Co-Authors David I. J