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All Journal Mikailalsys Journal of Advanced Engineering International Mikailalsys Journal of Mathematics and Statistics
Peter, Pantuvo Tsoke
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering

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Derivation of Two Parameters Poisson Rani Distribution and Its Properties Alao, Bamigbala Olateju; Peter, Pantuvo Tsoke; Babando, Ikrimat Aliyu; Gatta, Abdulganiy Abdullahi
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 1 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i1.4385

Abstract

This study introduces the Two Parameters Poisson Rani Distribution (TPPRD). The probability distribution of TPPRD is derived by assuming that the parameters of the Poisson distribution follow the Two Parameters Rani Distribution, resulting in the formation of the TPPRD. The study derives some of its fundamental properties and demonstrates that TPPRD is a special-case distribution capable of handling overdispersed count data. Additionally, the maximum likelihood estimators are used to derive equations for estimating the parameters of the Two Parameters Poisson Rani Distribution.
Forecasting Nigeria Inflation Rate Using Autoregressive Integrated Moving Average (ARIMA) Model Ikrimat, Aliyu; Akobi, Clement; Peter, Pantuvo Tsoke; Gatta, Abdulganiy Abdullahi
Mikailalsys Journal of Advanced Engineering International Vol 2 No 2 (2025): Mikailalsys Journal of Advanced Engineering International
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjaei.v2i2.5649

Abstract

This study focuses on forecasting Nigeria's inflation rate using the Autoregressive Integrated Moving Average (ARIMA) model. The research utilizes monthly inflation data from January 2010 to December 2024, obtained from the Central Bank of Nigeria (CBN). The primary objective is to model and forecast inflation trends in Nigeria, which has been experiencing significant inflationary pressures in recent years. The study employs the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests to check for stationarity, revealing that the inflation series becomes stationary after a second differencing (I (2)). The ARIMA (2,2,1) model is identified as the best fit based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), providing a balance between model complexity and predictive accuracy. The model reveals strong autoregressive and moving average dynamics, with significant coefficients for AR (1), AR (2), and MA (1) terms. The forecasted inflation rates for 2025 indicate a steady upward trend, with inflation expected to rise from 35.26% in January to 38.93% by December 2025. The findings highlight the persistent inflationary pressures in Nigeria, driven by factors such as currency depreciation, rising food prices, and energy costs. The study concludes that the ARIMA (2,2,1) model is effective for forecasting Nigeria's inflation rate and recommends that policymakers implement measures to stabilize the economy, including tighter monetary policies, fiscal discipline, and investments in domestic production to mitigate inflationary pressures. Continuous monitoring and timely adjustments to economic policies are also emphasized to address the ongoing challenges posed by inflation. Additionally, the study recommends diversifying the economy to reduce dependence on oil exports, improving agricultural productivity to curb food price volatility, and enhancing data collection methods for more accurate inflation forecasting.
Co-Authors Akobi, Clement Alao, Bamigbala Olateju Babando, Ikrimat Aliyu Gatta, Abdulganiy Abdullahi Ikrimat, Aliyu