ANOTHER WEIGHTED WEIBULL DISTRIBUTION FROM AZZALINI’S FAMILY

A new weighted Weibull distribution has been defined and studied. Some mathematical properties of the distribution have been studied and the method of maximum likelihood was proposed for estimating the parameters of the distribution. The usefulness of the new distribution was demonstrated by applying it to a real lifetime dataset

Predicting Customer Preference of Mobile Service using Neural Network

In countries where several Mobile Communication Service providers operate, it is imperative on the service providers to recognize the aspects of their services that will attract new customers in order to help them stay on top of the competition. This is known to be expensive in terms of money and time. To address this problem, we present a Feed-forward Back-propagation Neural Network (FBNN) that is aimed at learning potential customers’ “would-be” pattern of choosing a Mobile Service based on selected criteria. The Neural Network is tested on sample data and predictions made to the same effect as already mentioned. The results show that the Neural Network is adequate for predicting customer preference of a mobile service. This research concentrates on predicting new customer preferences as opposed to the popular notion of models predicting (existing) customer churn. Keywords: Feed-forward Back-propagation, Mobile Service Provider, Neural Network, Prediction

A Predictive Model for Monthly Currency in Circulation in Ghana

The Currency in Circulation is the outstanding amount of notes and coins circulated in the economy and are the most liquid monetary aggregate. In this study, secondary data on monthly Currency in Circulation obtained from the Bank of Ghana database was modelled using the Seasonal Autoregressive Integrated Moving Average model. The result revealed that ARIMA (0, 1, 1)(0, 1, 1)12 model was appropriate for modelling the Currency in Circulation. This model has the least AIC of -372.16, AICc of -371.97, and BIC of -363.53. Diagnostic test of the model residuals with the Ljung-Box and ARCH-LM test revealed that the model is free from higher order autocorrelation and conditional heteroscedasticity respectively. Thus, we proposed ARIMA (0, 1, 1)(0, 1, 1)12 model for predicting the Currency in Circulation in Ghana. However, continues monitoring of the forecasting performance of this model is necessary to make the use of this model more realistic. Keywords: Currency in Circulation, Liquidity, Monetary aggregat

The Efficacy of ARIMAX and SARIMA Models in Predicting Monthly Currency in Circulation in Ghana

In this study, the efficacy of the ARIMAX model and SARIMA model in forecasting the Currency in Circulation in Ghana was compared. Both models appear to be adequate for forecasting the Currency in Circulation. Diagnostic tests of both models with the Ljung-Box test and ARCH-LM test revealed that both models were free from higher-order serial correlation and conditional heteroscedasticity respectively. The Diebold-Mariano test revealed that there is no significant difference in the forecasting performance of the two models. Hence, both models were proposed for predicting the Currency in Circulation. However, we recommend that continues monitoring of the forecasting performance of these models, review of market conditions and necessary adjustments are vital to make the use of these models more realistic. Keywords: ARIMAX, SARIMA, Currency in Circulation, Ghana, forecastin

Monthly Effect on the Volume of Currency in Circulation in Ghana

In this study, the month-of–the-year effect on the volume of Currency in Circulation in Ghana was studied. The “New Year effect” was seen in the volume of Currency in Circulation as the first three months of the year clearly indicate a decrease in the volume of Currency in Circulation. The months of January, February and March decreases the volume of the Currency in Circulation by 7.4309, 5.0307 and 0.2112 percent respectively. The “December effect” was also seen in the volume of Currency in Circulation as the month of December had the highest incremental effect (18.6046%). The findings of the study also revealed that the seasonal changes in Currency in Circulation are a reflection of the effect of celebrative periods on Currency in Circulation. Keywords: Month-of-the-year, Currency in Circulation, Ghana, Liquidity managemen

Variable Control Charts Based on Percentiles of the New Weibull-Pareto Distribution

<p>A variable quality characteristic is assumed to follow the new weibull-Pareto distribution. Based on the evaluated percentiles of sample statistic like<br />mean, median, midrange, range and standard deviation, the control limits for the<br />respective control charts are developed . The admissibility and power of the control<br />limits is assessed in comparison with those based on the popular Shewhart control<br />limits.</p

Proposed Seasonal Autoregressive Integrated Moving Average Model for Forecasting Rainfall Pattern in the Navrongo Municipality, Ghana

Changes in rainfall pattern directly or indirectly affect various sectors like agricultural, insurance and other allied fields that play major roles in the development of any economy. An agrarian country like Ghana cannot do without rain because its agricultural sector heavily depends on rain water. In this study, the rainfall data was modelled using SARIMA model. The model identified to be adequate for forecasting the rainfall data was ARIMA (0, 0, 1)(0, 1, 1)12. An overall check of the model adequacy with the Ljung-Box revealed that this model was adequate for forecasting the rainfall data. Keywords: Navrongo, Ghana, SARIMA, Agricultural, forecastin

Modelling the Rate of Treasury Bills in Ghana

Treasury bills rate is a preeminent default-risk free rate asset in Ghana’s money market whose existence can affect the purchasing power of other assets in the security market. Bank of Ghana sells its Bills to mop up excess liquidity and buys Bank of Ghana Bills to inject liquidity into the system. This paper empirically models the monthly Treasury bill rate of two short term Treasury bills (91 day and 182 day) from the year 1998 to 2012 from the BoG using ARIMA models. From the results, it was realized that ARIMA  model is appropriate for modelling the 91-day Treasury bill rate with a log likelihood value of -328.58, and least AIC value of 667.17, AICc value of 667.52 and BIC value of 683.05. Also, ARIMA  best models the 182-day Treasury bill rates with a log likelihood value of -356.50, and AIC value of 717.00, AICc value of 717.06 and least BIC value of 723.35. An ARCH-LM test and Ljung-Box test on the residuals of the models revealed that the residuals are free from heteroscedasticity and serial correlation respectively. Keywords: Treasury bills, Ghana, Asset, Empirical, Short term

Effect of Chemically Modified Banana Fibers on the Mechanical Properties of Poly-Dimethyl-Siloxane-Based Composites

The study presents the mechanical properties of polymer-based composites reinforced with chemically modified banana fibers, by alkalization in different concentrations of sodium hydroxide (NaOH). The fiber weight fraction has a great effect on the mechanical properties of the composites. Stiff composites were obtained at 6 wt% fiber fractions with Young’s modulus of 254.00 ±12.70 MPa. Moreover, the yield strength was 35.70 ±1.79 MPa at 6 wt% fiber fractions. However, the ultimate tensile strength (UTS) and toughness of the composites were obtained at 5 wt% fiber fractions. Statistical analyses were used to ascertain the significant different on the mechanical properties of the fibers and composites. The implication of the results is then discussed for potential applications of PDMS-based composites reinforced with chemically modified banana fibers

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe