A new Maxwell-Log logistic distribution and its applications for mortality rate data Uthumporn Panitanarak, Aliyu Ismail Ishaq, Alfred Adewole Abiodun, Hanita Daud, Ahmad Abubakar Suleiman Journal of the Nigerian Society of Physical Sciences, 2025 In this research, we extended the Log-Logistic distribution by incorporating it into the Maxwell generalized class, resulting in the Maxwell-Log Logistic (Max-LL ) distribution. The probability density function and cumulative distribution function of the proposed distribution have been defined. The proposed distribution’s density shapes can be left or right-skewed and symmetric. The failure function of this distribution might be increasing, decreasing, or inverted bathtub forms. We discussed some essential properties of the Max-LL distribution, including moments, moment generating function, probability weighted moments, stress-strength, and order statistics. The efficiency of the model parameters has been evaluated through a simulation study utilizing a quantile function. To assess the proposed distribution’s adaptability, we applied it to two lifetime datasets: global COVID-19 mortality rates (for nations with more than 100,000 cases) and Canadian COVID-19 mortality rates. The Maxwell-Log Logistic distribution outperformed other distributions on both datasets, as evidenced by several accuracy measures. This shows that the proposed distribution is the best fit for COVID-19 mortality rate data in Canada and around the world.
Non-proportional hazard model without frailty and with frailty distribution under mixtures of baseline distribution Eunice Job, Alfred Abiodun International Conference on Science Engineering and Business for Driving Sustainable Development Goals Seb4sdg 2024, 2024 Proportional hazards (PH) model is one of the most commonly used methods in the analysis of time-to-event data. The assumption of (PH) model which states that the ratio of the hazards for any two individuals is constant over time may not hold if the hazard ratio varies with time. It is therefore necessary to use methods that do not assume proportionality to investigate the effects of covariates on survival time which leads us to non-proportional hazard (NPH) model. The PH model under frailty setting is a natural extension of the standard PH model to address the erroneous assumption that the baseline survival times are independently and identically distributed.This study compared non-proportional hazard (NPH) model without frailty and with frailty using Integrated Nested Laplace Approximation (INLA) method under the mixture of Weibull-Weibull, Lognormal-Lognormal and Weibull-Lognormal baseline distributions. Data were simulated from mixture of Weibull-Weibull, Lognormal-Lognormal and Weibull-Lognormal baseline hazard distributions for different sample sizes and censoring percentages. The NPH model without frailty and with frailty were then fitted to the data using Deviance Information Criterion (DIC) as the comparing metric.It was observed that the NPH model with frailty performed better than the NPH model without frailty in the three mixture of baseline distribution considered and also for all sample sizes and censoring percentages considered.
Modelling Nigerian Inflation Rates from January 2003 to June 2023 Using Newly Developed Inverse Power Chi-Square Distribution A. I. Ishaq, A. A. Abiodun, A. A. Suleiman, A. Usman, A. S. Mohammed, et al. 2023 4th International Conference on Data Analytics for Business and Industry Icdabi 2023, 2023 In developing nations like Nigeria, inflation impacts practically every aspect of the economy, and the expenses associated with it are substantial. The severity of the effects of inflation is determined by whether it was expected or unexpected. An expected inflation occurs when households and businesses can consistently forecast the future inflation rate at all times. However, unexpected inflation occurs when they are unable to estimate the future inflation rate. These measures are classified as monetary policy and fiscal policy. The use of statistical models in modelling and forecasting inflation is one of the most recent developments in economic and financial studies. In this study, a new continuous probability distribution is introduced that can be employed to model Nigerias inflation rate from January 2003 to June 2023. The distribution was developed by transforming the chi-square distribution with an additional parameter to unveil the inverse power chi-square distribution. The proposed model has a right and left-skewed form with increasing, constant, and decreasing failure rates, as can be seen from the density shapes. Some statistical properties and parameters of its estimates are examined. It was established that the suggested distribution was the most effective distribution for modeling Nigerias inflation rate.
On Maxwell–Lomax distribution: properties and applications Alfred Adewole Abiodun, Aliyu Ismail Ishaq Arab Journal of Basic and Applied Sciences, 2022 The development of new generalizations based on certain baseline probability distribution has become one of the current trends in distribution theory literature. New generators are often required to define wider distributions for modelling real life data. In this study, we proposed and studied a new generalization of Maxwell and Lomax distributions using the T-X method. Several structural and statistical properties of the proposed distribution were obtained such as moments, quantile function, survival and hazard functions, skewness, kurtosis and order statistics. The method of maximum likelihood estimation (MLE) was used to estimate the parameters of the proposed distribution. In addition, a simulation study was conducted to evaluate the performance of the MLE method. The proposed distribution was applied to two real life datasets to illustrate its flexibility. It was found that the proposed distribution was superior to offer a better fit than the other competing extensions of Lomax distributions considered in the study.
Modelling Nigerian Naira to CFA Franc Exchange Rates with Maxwell-Exponentiated Exponential distribution A. I. Ishaq, A. A. Abiodun, U. Panitanarak 2021 International Conference on Data Analytics for Business and Industry Icdabi 2021, 2021 In this study, a new statistical distribution, namely, the Maxwell-Exponentiated exponential distribution is developed in the application to financial data. This distribution serves as an alternative to Burr X-Exponentiated exponential, MarshallOlkin-Exponentiated Exponential and Type II Half Logistic-Exponentiated Exponential distributions. The quantile function of the proposed distribution was obtained. Some statistical properties and estimates of their parameters were studied. The performance of proposed distribution was carried out by using application to the data set relating to monthly Nigerian naira to CFA Franc exchange rate. The results showed that the proposed Maxwell-Exponentiated exponential distribution was chosen as the best fitted monthly Nigerian naira to CFA Franc exchange rate data by having a minimum values of AIC and CAIC.
