Time series based road traffic accidents forecasting via SARIMA and Facebook Prophet model with potential changepoints.

Road traffic accident (RTA) is a critical global public health concern, particularly in developing countries. Analyzing past fatalities and predicting future trends is vital for the development of road safety policies and regulations. The main objective of this study is to assess the effectiveness of univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) and Facebook (FB) Prophet models, with potential change points, in handling time-series road accident data involving seasonal patterns in contrast to other statistical methods employed by key governmental agencies such as Ghana's Motor Transport and Traffic Unit (MTTU).

Baseline comparative analysis and review of election forensics: Application to Ghana's 2012 and 2020 presidential elections.

Many allegations have been levelled against the electoral process of many countries across the world by most opposition leaders, especially when they lose a presidential election e.g. Ghana in 2012 and 2020.

Statistical Modeling of HIV, Tuberculosis, and Hepatitis B Transmission in Ghana.

Most mortality studies usually attribute death to single disease, while various other diseases could also act in the same individual or a population at large. Few works have been done by considering HIV, Tuberculosis (TB), and Hepatitis B (HB) as jointly acting in a population in spite of their high rate of infections in Ghana. This study applied competing risk methods on these three diseases by assuming they were the major risks in the study population.

Markov Chain Modeling of HIV, Tuberculosis, and Hepatitis B Transmission in Ghana.

Several mathematical and standard epidemiological models have been proposed in studying infectious disease dynamics. These models help to understand the spread of disease infections. However, most of these models are not able to estimate other relevant disease metrics such as probability of first infection and recovery as well as the expected time to infection and recovery for both susceptible and infected individuals.

Socioeconomic Status and Temporal Urban Environmental Change in Accra: a Comparative Analysis of Area-based Socioeconomic and Urban Environmental Quality Conditions Between Two Time Points.

The influence of area-based socioeconomic (SE) conditions on environmental quality conditions has recently been reported showing the precise spatial relationship between area-based SE conditions and neighborhood environmental quality in an urban area in a low-income setting. Nonetheless, there is still a lack of understanding of the nature of the relationship on a temporal scale. This study aimed to investigate the dynamic temporal relationship between area-based SE conditions and urban environmental quality conditions over a decadal period in Accra, Ghana.

Erratum to: Estimation of the Gini coefficient for the lognormal distribution of income using the Lorenz curve.

[This corrects the article DOI: 10.1186/s40064-016-2868-z.].

Estimation of the Gini coefficient for the lognormal distribution of income using the Lorenz curve.

The main objective of the study is to compare the Newton-Cotes methods such as the Trapezium rule, Simpson 1/3 rule and Simpson 3/8 rule to estimate the area under the Lorenz curve and Gini coefficient of income using polynomial function with degree 5. Comparing the Gini coefficients of income computed from the Polynomial function with degree 5 for the Trapezium, Simpson 1/3 and Simpson 3/8 methods using the relative errors showed that the trapezium rule, Simpson's 1/3 rule and Simpson's 3/8 rule show negative biases with the Simpson 1/3 rule yielding the lowest absolute relative true error of 4.230711 %.

Extreme value modelling of Ghana stock exchange index.

Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data.

A Markov chain Monte Carlo (MCMC) methodology with bootstrap percentile estimates for predicting presidential election results in Ghana.

Although, there exists numerous literature on the procedure for forecasting or predicting election results, in Ghana only opinion poll strategies have been used. To fill this gap, the paper develops Markov chain models for forecasting the 2016 presidential election results at the Regional, Zonal (i.e.

Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models.

This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications.