Research Articles (Mathematical Statistics and Actuarial Science)
Permanent URI for this collection
Browse
Recent Submissions
Item Open Access Quantile regression analysis of modifiable and non-modifiable predictors of stroke among adults in South Africa(Bentham Open, 2021) Chikobvu, Delson; Matizirofa, Lynn'sBackground: Stroke is the second largest cause of mortality and long-term disability in South Africa (SA). Stroke is a multifactorial disease regulated by modifiable and non-modifiable predictors. Little is known about the stroke predictors in SA, particularly modifiable and non-modifiable. Identification of stroke predictors using appropriate statistical methods can help formulate appropriate health programs and policies aimed at reducing the stroke burden. This study aims to address important gaps in stroke literature i.e., identifying and quantifying stroke predictors through quantile regression analysis. Methods: A cross-sectional hospital-based study was used to identify and quantify stroke predictors in SA using 35730 individual patient data retrieved from selected private and public hospitals between January 2014 and December 2018. Ordinary logistic regression models often miss critical aspects of the relationship that may exist between stroke and its predictors. Quantile regression analysis was used to model the effects of each predictor on stroke distribution. Results: Of the 35730 cases of stroke, 22183 were diabetic. The dominant stroke predictors were diabetes, hypertension, heart problems, the female gender, higher age groups and black race. The age group 55-75 years, female gender and black race, had a bigger effect on stroke distribution at the lower upper quantiles. Diabetes, hypertension and cholesterol showed a significant impact on stroke distribution (p < 0.0001). Conclusion: Most strokes are attributable to modifiable factors. Study findings will be used to raise awareness of modifiable predictors to prevent strokes. Regular screening and treatment are recommended for high-risk individuals with identified predictors in SA.Item Open Access Soil fertilization synergistically enhances the impact of pollination services in increasing seed yield of sunflower under dryland conditions(Cambridge University Press, 2021) Adelabu, Dollop Bola; Bredenhand, Emile; Van der Merwe, Sean; Franke, Angelinus CorneliusTo exploit the potential of ecological intensification during sunflower cropping, it is crucial to understand the potential synergies between crop management and ecosystem services. We therefore examined the effect of pollination intensification on sunflower yield and productivity under various levels of soil fertilization over two seasons in the eastern Free State, South Africa. We manipulated soil fertility with fertilizer applications and pollination with exclusion bags. We found a synergetic effect between pollination and soil fertilization whereby increasing pollination intensity led to a far higher impact on sunflower yield when the soil had been fertilized. Specifically, the intensification of insect pollination increased seed yield by approximately 0.4 ton/ha on nutrient poor soil and by approximately 1.7 ton/ha on moderately fertilized soil. Our findings suggest that sunflower crops on adequate balanced soil fertility will receive abundant insect pollination and may gain more from both synergies than crops grown in areas with degraded soil fertility.Item Open Access Modelling international tourist arrivals volatility in Zimbabwe using a GARCH process(AfricaJournals, 2021) Makoni, Tendi; Chikobvu, DelsonThe aim of the paper was to develop bootstrap prediction intervals for international tourism demand and volatility in Zimbabwe after modelling with an ARMA-GARCH process. ARMA-GARCH models have better forecasting power and are capable of capturing and quantifying volatility. Bootstrap prediction intervals can account for future uncertainty that arises through parameter estimation. The monthly international tourism data obtained from the Zimbabwe Tourism Authority (ZTA) (January 2000 to June 2017) is neither seasonal nor stationary and is made stationery by taking a logarithm transformation. An ARMA(1,1) model fits well to the data; with forecasts indicating a slow increase in international tourist arrivals (outside of the Covid-19 period). The GARCH(1,1) process indicated that unexpected tourism shocks will significantly impact the Zimbabwe international tourist arrivals for longer durations. Volatility bootstrap prediction intervals indicated minimal future uncertainty in international tourist arrivals. For the Zimbabwe tourism industry to remain relevant, new tourism products and attraction centres need to be developed, as well as embarking on effective marketing strategies to lure even more tourists from abroad. This will go a long way in increasing the much-needed foreign currency earnings needed to revive the Zimbabwean economy.Item Open Access Performance of first-year accounting students: does time perspective matter?(University of the Free State, 2013) Joubert, Hanli; Viljoen, Marianne; Schall, RobertEnglish: Academic failure of first-year accounting students is a national and international problem. Existing research is inconclusive regarding the causes for the failure and does not make provision for the possible influence of dominant time perspectives on performance in accounting. This article investigates whether time perspective has an effect on the performance of first-year accounting students. A quantitative non-experimental predictive multivariate design is used and confounding variables are taken into consideration. The results of the study indicate significant relationships between performance in first-year accounting and gender, age and a past-negative time perspective. The most significant result of this study is that a past-negative time perspective, together with an unfavourable psychosocial background, might have led to failure in first-year accounting. It is suggested that students with a negative time perspective be identified and encouraged to participate in support programmes at the university.