Browsing by Author "Owino, Abraham"

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    Determining Food Insecurity: An Application of the Rasch Model with Household Survey Data in Uganda
    (International journal of food science, 2014) Owino, Abraham; Wesonga, Ronald; Nabugoomu, Fabian
    The inexplicable nature of food insecurity in parts of Uganda and worldwide necessitated an investigation into the nature, extent, and differentials of household food security.Themain objective of this study was to examine the food security dynamics and model household food insecurity.The Raschmodelling approach was employed on a dataset froma sample of 1175 (Tororo = 577; Busia = 598) randomly selected households in the year 2010. All households provided responses to the food security questions and none was omitted from the analysis. At 5 percent level of significance the analysis indicated that Tororo district average food security assessment (0.137 ± 0.181) was lower than that for Busia district (0.768 ± 0.177). All the mean square fit statistics were in the range of 0.5 to 1.5, and none of them showed any signs of distortion, degradation, or less productivity formeasurement.This confirmed that items used in this study were very productive for measurement of food security in the study area.The study recommends further analysis where item responses are ordered polytomous rather than the dichotomous item response functions used. Furthermore, consideration should be given to fit models that allow for different latent distributions for households with children and those without children and possibly other subgroups of respondents.
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    Logit models for household food insecurity classification
    (American Journal of Theoretical and Applied Statistics, 2014) Owino, Abraham; Kiboijana Atuhaire, Leonard; Wesonga, Ronald; Nabugoomu, Fabian; Muwanga-Zaake, Elijah
    Micro-level measurement of food insecurity is a necessary approach towards a more feasible solution to the global problem for proper classification of households by food insecurity status. Measurement of food insecurity is a challenge because it is a multi-faceted latent and continuous phenomenon explained by a wide range of both quantitative and qualitative variables. In this paper, we examined the quantitative variables and applied exploratory factor analysis to identify which of them significantly influence household food insecurity. Logit models were then developed using the variables identified. Further, empirical data obtained from Tororo and Busia rural households in Uganda were used to fit the models. Four logit models based on four scenarios were developed and compared. The key findings pointed to the fact that if households were to be correctly analyzed and classified into the right food security category, a hybrid dependent variable that represents as many aspects of food insecurity as possible should be used. The model correctly classified 90 % of the combined households for two districts. However, when fitted for separate districts, it was established that 99% of households in Busia and 96% in Tororo district respectively, were found to be food insecure.
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    Simulation of time series wind speed at an international airport
    (Simulation, 2019) Wesonga, Ronald; Nabugoomu, Fabian; Ababneh, Faisal; Owino, Abraham
    The sporadic and unstable nature of wind speed renders it very difficult to predict accurately to serve various decisions, such as safety in the air traffic flow and reliable power generation system. In this study we assessed the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models on the wind speed time series problem. Data on wind speed and minimum and maximum temperatures were evaluated. Wind speed was established to follow a time series that fluctuated around ARIMA (0,1,1) and ARIMA (1,1,1). The optimal ANN model was established at 10 hidden neurons. The performance indices considered all indicated that the ANN wind speed model was superior to the ARIMA model. Wind speed prediction accuracy can be improved to secure the safety of air traffic flow as well support the implementation of a reliable and secure power generation system at the airport